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Sample records for adaptive landscape classification

  1. Adaptive Classification of Landscape Process and Function: An Integration of Geoinformatics and Self-Organizing Maps

    SciTech Connect

    Coleman, Andre M.

    2009-07-17

    The advanced geospatial information extraction and analysis capabilities of a Geographic Information System (GISs) and Artificial Neural Networks (ANNs), particularly Self-Organizing Maps (SOMs), provide a topology-preserving means for reducing and understanding complex data relationships in the landscape. The Adaptive Landscape Classification Procedure (ALCP) is presented as an adaptive and evolutionary capability where varying types of data can be assimilated to address different management needs such as hydrologic response, erosion potential, habitat structure, instrumentation placement, and various forecast or what-if scenarios. This paper defines how the evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight into complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Establishing relationships among high-dimensional datasets through neurocomputing based pattern recognition methods can help 1) resolve large volumes of data into a structured and meaningful form; 2) provide an approach for inferring landscape processes in areas that have limited data available but exhibit similar landscape characteristics; and 3) discover the value of individual variables or groups of variables that contribute to specific processes in the landscape. Classification of hydrologic patterns in the landscape is demonstrated.

  2. An Adaptive Landscape Classification Procedure using Geoinformatics and Artificial Neural Networks

    SciTech Connect

    Coleman, Andre Michael

    2008-06-01

    The Adaptive Landscape Classification Procedure (ALCP), which links the advanced geospatial analysis capabilities of Geographic Information Systems (GISs) and Artificial Neural Networks (ANNs) and particularly Self-Organizing Maps (SOMs), is proposed as a method for establishing and reducing complex data relationships. Its adaptive and evolutionary capability is evaluated for situations where varying types of data can be combined to address different prediction and/or management needs such as hydrologic response, water quality, aquatic habitat, groundwater recharge, land use, instrumentation placement, and forecast scenarios. The research presented here documents and presents favorable results of a procedure that aims to be a powerful and flexible spatial data classifier that fuses the strengths of geoinformatics and the intelligence of SOMs to provide data patterns and spatial information for environmental managers and researchers. This research shows how evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight into complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Certainly, environmental management and research within heterogeneous watersheds provide challenges for consistent evaluation and understanding of system functions. For instance, watersheds over a range of scales are likely to exhibit varying levels of diversity in their characteristics of climate, hydrology, physiography, ecology, and anthropogenic influence. Furthermore, it has become evident that understanding and analyzing these diverse systems can be difficult not only because of varying natural characteristics, but also because of the availability, quality, and variability of spatial and temporal data. Developments in geospatial technologies, however, are providing a wide range of relevant data, and in many cases, at a high temporal and spatial resolution. Such data resources can take the form of high

  3. [Landscape classification: research progress and development trend].

    PubMed

    Liang, Fa-Chao; Liu, Li-Ming

    2011-06-01

    Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

  4. From landscape to domain: Soils role in landscape classifications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil landscape classifications are designed to divide landscapes into units with significance for the provisioning and regulating of ecosystem services and the development of conservation plans for natural resources. More specifically, such classifications serve as the basis for stratifying manageme...

  5. Adaptive Gaussian Pattern Classification

    DTIC Science & Technology

    1988-08-01

    redundant model of the data to be used in classification . There are two classes of learning, or adaptation schemes. The first, unsupervised learning...37, No. 3, pp. 242-247, 1983. [2] E. F. Codd, Cellular Automata , Academic Press, 1968. [31 H. Everett, G. Gilbreath, S. Alderson, D. J. Marchette...Na al Oca aytm aete !JTI FL E COPY AD-A 199 030 Technical Document 1335 August 1988 Adaptive Gaussian Pattern Classif ication C. E. Priebe D. J

  6. [Wetland landscape ecological classification: research progress].

    PubMed

    Cao, Yu; Mo, Li-jiang; Li, Yan; Zhang, Wen-mei

    2009-12-01

    Wetland landscape ecological classification, as a basis for the studies of wetland landscape ecology, directly affects the precision and effectiveness of wetland-related research. Based on the history, current status, and latest progress in the studies on the theories, indicators, and methods of wetland landscape classification, some scientific wetland classification systems, e.g., NWI, Ramsar, and HGM, were introduced and discussed in this paper. It was suggested that a comprehensive classification method based on HGM and on the integral consideration of wetlands spatial structure, ecological function, ecological process, topography, soil, vegetation, hydrology, and human disturbance intensity should be the major future direction in this research field. Furthermore, the integration of 3S technologies, quantitative mathematics, landscape modeling, knowledge engineering, and artificial intelligence to enhance the automatization and precision of wetland landscape ecological classification would be the key issues and difficult topics in the studies of wetland landscape ecological classification.

  7. Oregon Hydrologic Landscapes: A Classification Framework

    EPA Science Inventory

    There is a growing need for hydrologic classification systems that can provide a basis for broad-scale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. We developed a hydrologic landscape (HL) classifica...

  8. Hydrologic Landscape Classification to Estimate Bristol Bay Watershed Hydrology

    EPA Science Inventory

    The use of hydrologic landscapes has proven to be a useful tool for broad scale assessment and classification of landscapes across the United States. These classification systems help organize larger geographical areas into areas of similar hydrologic characteristics based on cl...

  9. ASSESSMENT OF LANDSCAPE CHARACTERISTICS ON THEMATIC IMAGE CLASSIFICATION ACCURACY

    EPA Science Inventory

    Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of misclassifying pixels during thematic image classification. However, there has been a lack of empirical evidence, to support these hypotheses. This...

  10. Hydrologic classification of Bristol Bay, Alaska using hydrologic landscapes

    NASA Astrophysics Data System (ADS)

    Todd, J.; Wigington, P. J.; Sproles, E.

    2013-12-01

    The use of hydrologic landscapes has proven to be a useful tool for broad scale assessment and classification of landscapes across the United States. These classification systems help organize larger geographical areas into areas of similar hydrologic characteristics based on climate, terrain and underlying geology. Such characterization of landscapes into areas of common hydrologic patterning is particularly instructive in regions where site specific hydrologic data is sparse or spatially incomplete. By using broad scale landscape metrics to organize the landscape into discrete, characterized units, natural resources managers can gain valuable understanding of landscape patterning and how locations may be differentially affected by a variety of environmental stressors ranging from land use change to management of salmon resources to climate change. Further, the heterogeneity of aquatic habitats and undisturbed hydrologic regimes within this area are a known principal driver for its region-wide fisheries stability. The use of hydrologic landscapes offers an opportunity to better characterize the hydrologic and landscape influences on structuring biotic populations at a regional scale. We have undertaken a hydrologic landscape approach for the Bristol Bay region of Alaska to gain a better understanding of the overall hydrologic environment found in this region since its hydrologic patterning plays a principal role in structuring its world-renowned salmon fishery. Heretofore, a characterization of the entire Bristol Bay region into discrete hydrologic units has not been undertaken. Our classification structure includes indices of annual climate and seasonality, terrain, and geology. Following categorization of landscape units, we compared hydrologic landscape units to locations of available long term streamflow for characterization of expected hydrologic behavior. This demonstration of hydrologic landscapes in Bristol Bay, Alaska shows the utility of using large

  11. Hydrologic Classification of Bristol Bay, Alaska Using Hydrologic Landscapes

    NASA Astrophysics Data System (ADS)

    Todd, J.; Wigington, P. J., Jr.; Sproles, E. A.

    2014-12-01

    The use of hydrologic landscapes has proven to be a useful tool for broad scale assessment and classification of landscapes across the United States. These classification systems help organize larger geographical areas into areas of similar hydrologic characteristics based on climate, terrain and underlying geology. Such characterization of landscapes into areas of common hydrologic patterning is particularly instructive where site specific hydrologic data is sparse or spatially incomplete. By using broad scale landscape metrics to organize the landscape into discrete, characterized units, natural resources managers can gain valuable understanding of landscape patterning and how locations may be differentially affected by a variety of environmental stressors ranging from land use change to climate change. The heterogeneity of aquatic habitats and undisturbed hydrologic regimes within Bristol Bay are a known principal driver for its overall fisheries stability and the use of hydrologic landscapes offers the ability to better characterize the hydrologic and landscape influences on structuring biotic populations at a regional scale. Here we classify the entire Bristol Bay region into discrete hydrologic landscape units based on indices of annual climate and seasonality, terrain, and geology. We then compared hydrologic landscape units to locations of available long term streamflow for characterization of expected hydrologic behavior where streamflow data was lacking. This demonstration of hydrologic landscapes in Bristol Bay, Alaska shows the utility of using large-scale datasets on climate, terrain and geology to infer broad scale hydrologic patterning within a data poor area. Disclaimer: The authors' views expressed here do not necessarily reflect views or policies of USEPA.

  12. The sensory ecology of adaptive landscapes

    PubMed Central

    Jordan, Lyndon A.; Ryan, Michael J.

    2015-01-01

    In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions about adaptive behaviour and what is behaviourally achievable given the umwelt of the animal being studied. This may lead to erroneous conclusions about maladaptive behaviour in circumstances when the behaviour exhibited is the most adaptive possible given sensory limitations. With advances in the computational resources available to behavioural ecologists, we can now measure vast numbers of interactions among behaviours and environments to create adaptive behavioural surfaces. These surfaces have massive heuristic, predictive and analytical potential in understanding adaptive animal behaviour, but researchers using them are destined to fail if they ignore the sensory ecology of the species they study. Here, we advocate the continued use of these approaches while directly linking them to perceptual space to ensure that the topology of the generated adaptive landscape matches the perceptual reality of the animal it intends to study. Doing so will allow predictive models of animal behaviour to reflect the reality faced by the agents on adaptive surfaces, vastly improving our ability to determine what constitutes an adaptive response for the animal in question. PMID:26018831

  13. Seri Landscape Classification and Spatial Reference

    ERIC Educational Resources Information Center

    O'Meara, Carolyn

    2010-01-01

    This thesis contributes to the growing field of ethnophysiography, a new subfield of cognitive anthropology that aims to determine the universals and variation in the categorization of landscape objects across cultures. More specifically, this work looks at the case of the Seri people of Sonora, Mexico to investigate the way they categorize…

  14. Regulated superinfection may help HIV adaptation on rugged landscape.

    PubMed

    Leontiev, Vladimir; Hadany, Lilach

    2010-05-01

    Human immunodeficiency virus (HIV) is highly adaptable to a, changing environment, including host immune response and antiviral drugs. Superinfection occurs when several HIV proviruses share the same host cell. We previously proposed that HIV may regulate the rate of its superinfection, which would help the virus to adapt (Leontiev et al., 2008). In this paper we, investigate the effect of regulated superinfection in HIV on complex, adaptation on rugged fitness landscapes. We present the results of our in silico experiments that suggest that regulated superinfection facilitates HIV, adaptation on rugged fitness landscapes and that the advantage of regulated, superinfection increases with the ruggedness of the landscape.

  15. Ecological Landscape Classification Using Astronaut Photography

    NASA Astrophysics Data System (ADS)

    Stefanov, W. L.; Castle, J. V.

    2006-12-01

    Digital astronaut photography acquired from the International Space Station is a potentially useful dataset for ecologic, geologic, and land use/land cover studies as it varies greatly in resolution (6 m/pixel minimum) and temporal frequency (minimum 1 day repeat cycle). The entire digital astronaut dataset is freely available from http://eol.jsc.nasa.gov. The dataset includes imagery from 1961 to present, and includes data for much of the Earth's surface. The National Science Foundation's Long Term Ecological Research (LTER) Network provides an ideal framework for assessment of the quantitative potential of digital astronaut photography. The Network of 26 sites represent a wide range of biomes including temperate and tropical forest, deserts, grasslands, tundra, and urban human-dominated ecosystems. This wide range of sites provides an excellent database for comparison of digital astronaut photography with remotely sensed data (i.e. Landsat) as well as field-based validation and measurement data. Used with remotely-sensed satellite and airborne data, digital astronaut photography can increase the temporal resolution of observed variables such as land cover, land use change, vegetation dynamics, and surface soil processes. In contrast to traditional narrow bandwidth remote sensing instruments, digital astronaut photography is acquired using off-the-shelf digital cameras sensitive to the visible red, green, and blue wavelengths; decisions to acquire imagery are made on-the-fly by the astronaut. The wide bandpasses of the camera make traditional classification approaches difficult as discrete spectral information is not typically obtained. We apply a multilevel, object-oriented image segmentation approach to high resolution digital astronaut photography of LTER sites representing a range of continental and island biomes. This approach emphasizes spatial relationships of similar pixels in addition to spectral information. Results include comparison of classification

  16. Hydrologic landscape regionalisation using deductive classification and random forests.

    PubMed

    Brown, Stuart C; Lester, Rebecca E; Versace, Vincent L; Fawcett, Jonathon; Laurenson, Laurie

    2014-01-01

    Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of

  17. Hydrologic Landscape Regionalisation Using Deductive Classification and Random Forests

    PubMed Central

    Brown, Stuart C.; Lester, Rebecca E.; Versace, Vincent L.; Fawcett, Jonathon; Laurenson, Laurie

    2014-01-01

    Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of

  18. Selection Limits to Adaptive Walks on Correlated Landscapes

    PubMed Central

    Heredia, Jorge Pérez; Trubenová, Barbora; Sudholt, Dirk; Paixão, Tiago

    2017-01-01

    Adaptation depends critically on the effects of new mutations and their dependency on the genetic background in which they occur. These two factors can be summarized by the fitness landscape. However, it would require testing all mutations in all backgrounds, making the definition and analysis of fitness landscapes mostly inaccessible. Instead of postulating a particular fitness landscape, we address this problem by considering general classes of landscapes and calculating an upper limit for the time it takes for a population to reach a fitness peak, circumventing the need to have full knowledge about the fitness landscape. We analyze populations in the weak-mutation regime and characterize the conditions that enable them to quickly reach the fitness peak as a function of the number of sites under selection. We show that for additive landscapes there is a critical selection strength enabling populations to reach high-fitness genotypes, regardless of the distribution of effects. This threshold scales with the number of sites under selection, effectively setting a limit to adaptation, and results from the inevitable increase in deleterious mutational pressure as the population adapts in a space of discrete genotypes. Furthermore, we show that for the class of all unimodal landscapes this condition is sufficient but not necessary for rapid adaptation, as in some highly epistatic landscapes the critical strength does not depend on the number of sites under selection; effectively removing this barrier to adaptation. PMID:27881471

  19. Adaptive multiclass classification for brain computer interfaces.

    PubMed

    Llera, A; Gómez, V; Kappen, H J

    2014-06-01

    We consider the problem of multiclass adaptive classification for brain-computer interfaces and propose the use of multiclass pooled mean linear discriminant analysis (MPMLDA), a multiclass generalization of the adaptation rule introduced by Vidaurre, Kawanabe, von Bünau, Blankertz, and Müller (2010) for the binary class setting. Using publicly available EEG data sets and tangent space mapping (Barachant, Bonnet, Congedo, & Jutten, 2012) as a feature extractor, we demonstrate that MPMLDA can significantly outperform state-of-the-art multiclass static and adaptive methods. Furthermore, efficient learning rates can be achieved using data from different subjects.

  20. Transcriptome analysis reveals signature of adaptation to landscape fragmentation.

    PubMed

    Somervuo, Panu; Kvist, Jouni; Ikonen, Suvi; Auvinen, Petri; Paulin, Lars; Koskinen, Patrik; Holm, Liisa; Taipale, Minna; Duplouy, Anne; Ruokolainen, Annukka; Saarnio, Suvi; Sirén, Jukka; Kohonen, Jukka; Corander, Jukka; Frilander, Mikko J; Ahola, Virpi; Hanski, Ilkka

    2014-01-01

    We characterize allelic and gene expression variation between populations of the Glanville fritillary butterfly (Melitaea cinxia) from two fragmented and two continuous landscapes in northern Europe. The populations exhibit significant differences in their life history traits, e.g. butterflies from fragmented landscapes have higher flight metabolic rate and dispersal rate in the field, and higher larval growth rate, than butterflies from continuous landscapes. In fragmented landscapes, local populations are small and have a high risk of local extinction, and hence the long-term persistence at the landscape level is based on frequent re-colonization of vacant habitat patches, which is predicted to select for increased dispersal rate. Using RNA-seq data and a common garden experiment, we found that a large number of genes (1,841) were differentially expressed between the landscape types. Hexamerin genes, the expression of which has previously been shown to have high heritability and which correlate strongly with larval development time in the Glanville fritillary, had higher expression in fragmented than continuous landscapes. Genes that were more highly expressed in butterflies from newly-established than old local populations within a fragmented landscape were also more highly expressed, at the landscape level, in fragmented than continuous landscapes. This result suggests that recurrent extinctions and re-colonizations in fragmented landscapes select a for specific expression profile. Genes that were significantly up-regulated following an experimental flight treatment had higher basal expression in fragmented landscapes, indicating that these butterflies are genetically primed for frequent flight. Active flight causes oxidative stress, but butterflies from fragmented landscapes were more tolerant of hypoxia. We conclude that differences in gene expression between the landscape types reflect genomic adaptations to landscape fragmentation.

  1. Efficient retrieval of landscape Hessian: Forced optimal covariance adaptive learning

    NASA Astrophysics Data System (ADS)

    Shir, Ofer M.; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳104). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  2. Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.

    PubMed

    Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  3. Adaptive landscapes: Top-down and bottom-up perspectives

    NASA Astrophysics Data System (ADS)

    Kerr, Benjamin

    Sewall Wright introduced the metaphor of the adaptive landscape, a map from genotype to fitness, more than 80 years ago to help describe his view of adaptive evolution. This metaphor has been immensely popular and has been used in a variety of incarnations. However, a systematic study of the genotype-fitness map presents significant problems. The space of possible genotypes is vast, and the mapping is likely dependent on both environment and the composition of genotypes in a population. In this talk, I will discuss some of these problems and present experimental strategies for uncovering features of adaptive landscapes. In particular, I will discuss how population structure can be used as an experimental variable to elucidate landscape topography and how a combination of experimental evolution and genetic engineering can reveal important landscape features in changing environments. I will also present some potential applications of this work to the problem of antibiotic resistance and potential implications for evolutionary rescue in the face of global climate change. For some of these topics, the classic notion of the adaptive landscape must itself be adapted; however, I propose that there are fruitful ways to continue to apply this metaphor.

  4. Rugged adaptive landscapes shape a complex, sympatric radiation

    PubMed Central

    Pfaender, Jobst; Hadiaty, Renny K.; Schliewen, Ulrich K.; Herder, Fabian

    2016-01-01

    Strong disruptive ecological selection can initiate speciation, even in the absence of physical isolation of diverging populations. Species evolving under disruptive ecological selection are expected to be ecologically distinct but, at least initially, genetically weakly differentiated. Strong selection and the associated fitness advantages of narrowly adapted individuals, coupled with assortative mating, are predicted to overcome the homogenizing effects of gene flow. Theoretical plausibility is, however, contrasted by limited evidence for the existence of rugged adaptive landscapes in nature. We found evidence for multiple, disruptive ecological selection regimes that have promoted divergence in the sympatric, incipient radiation of ‘sharpfin’ sailfin silverside fishes in ancient Lake Matano (Sulawesi, Indonesia). Various modes of ecological specialization have led to adaptive morphological differences between the species, and differently adapted morphs display significant but incomplete reproductive isolation. Individual fitness and variation in morphological key characters show that disruptive selection shapes a rugged adaptive landscape in this small but complex incipient lake fish radiation. PMID:26763702

  5. Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

  6. Dynamic LiDAR-NDVI classification of fluvial landscape units

    NASA Astrophysics Data System (ADS)

    Ramírez-Núñez, Carolina; Parrot, Jean-François

    2015-04-01

    The lower basin of the Coatzacoalcos River is a wide floodplain in which, during the wet season, local and major flooding are distinguished. Both types of floods, intermittent and regional, are important in terms of resources; the regional flood sediments enrich the soils of the plains and intermittent floods allow obtaining aquatic resources for subsistence during the heatwave. In the floodplain different abandoned meanders and intermittent streams are quickly colonized by aquatic vegetation. However, from the 1990s, the Coatzacoalcos River floodplain has important topographic changes due to mining, road and bridges construction; erosion and sedimentation requires continuous parcel boundaries along with the increasing demand of channel reparation, embankments, levees and bridges associated to tributaries. NDVI data, LiDAR point cloud and various types of flood simulations taking into account the DTM are used to classify the dynamic landscape units. These units are associated to floods in relation with water resources, agriculture and livestock. In the study area, the first returns of the point cloud allow extracting vegetation strata. The last returns correspond to the bare earth surface, especially in this area with few human settlements. The surface that is not covered by trees or by aquatic vegetation, correspond to crops, pastures and bare soils. The classification is obtained by using the NDVI index coupled with vegetation strata and water bodies. The result shows that 47.96% of the area does not present active vegetation and it includes 31.53% of bare soils. Concerning the active vegetation, pastures, bushes and trees represent respectively 25.59%, 11.14% and 13.25%. The remaining 1.25% is distributed between water bodies with aquatic vegetation, trees and shrubs. Dynamic landscape units' classification represents a tool for monitoring water resources in a fluvial plain. This approach can be also applied to forest management, environmental services and

  7. Adaptation with gene flow across the landscape in a dune sunflower.

    PubMed

    Andrew, Rose L; Ostevik, Katherine L; Ebert, Daniel P; Rieseberg, Loren H

    2012-05-01

    Isolation by adaptation increases divergence at neutral loci when natural selection against immigrants reduces the rate of gene flow between different habitats. This can occur early in the process of adaptive divergence and is a key feature of ecological speciation. Despite the ability of isolation by distance (IBD) and other forms of landscape resistance to produce similar patterns of neutral divergence within species, few studies have used landscape genetics to control for these other forces. We have studied the divergence of Helianthus petiolaris ecotypes living in active sand dunes and adjacent non-dune habitat, using landscape genetics approaches, such as circuit theory and multiple regression of distance matrices, in addition to coalescent modelling. Divergence between habitats was significant, but not strong, and was shaped by IBD. We expected that increased resistance owing to patchy and unfavourable habitat in the dunes would contribute to divergence. Instead, we found that landscape resistance models with lower resistance in the dunes performed well as predictors of genetic distances among subpopulations. Nevertheless, habitat class remained a strong predictor of genetic distance when controlling for isolation by resistance and IBD. We also measured environmental variables at each site and confirmed that specific variables, especially soil nitrogen and vegetation cover, explained a greater proportion of variance in genetic distance than did landscape or the habitat classification alone. Asymmetry in effective population sizes and numbers of migrants per generation was detected using coalescent modelling with Bayesian inference, which is consistent with incipient ecological speciation being driven by the dune habitat.

  8. Gap Shape Classification using Landscape Indices and Multivariate Statistics

    NASA Astrophysics Data System (ADS)

    Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

    2016-11-01

    This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

  9. Gap Shape Classification using Landscape Indices and Multivariate Statistics

    PubMed Central

    Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

    2016-01-01

    This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

  10. Adaptive Landscapes of Resistance Genes Change as Antibiotic Concentrations Change.

    PubMed

    Mira, Portia M; Meza, Juan C; Nandipati, Anna; Barlow, Miriam

    2015-10-01

    Most studies on the evolution of antibiotic resistance are focused on selection for resistance at lethal antibiotic concentrations, which has allowed the detection of mutant strains that show strong phenotypic traits. However, solely focusing on lethal concentrations of antibiotics narrowly limits our perspective of antibiotic resistance evolution. New high-resolution competition assays have shown that resistant bacteria are selected at relatively low concentrations of antibiotics. This finding is important because sublethal concentrations of antibiotics are found widely in patients undergoing antibiotic therapies, and in nonmedical conditions such as wastewater treatment plants, and food and water used in agriculture and farming. To understand the impacts of sublethal concentrations on selection, we measured 30 adaptive landscapes for a set of TEM β-lactamases containing all combinations of the four amino acid substitutions that exist in TEM-50 for 15 β-lactam antibiotics at multiple concentrations. We found that there are many evolutionary pathways within this collection of landscapes that lead to nearly every TEM-genotype that we studied. While it is known that the pathways change depending on the type of β-lactam, this study demonstrates that the landscapes including fitness optima also change dramatically as the concentrations of antibiotics change. Based on these results we conclude that the presence of multiple concentrations of β-lactams in an environment result in many different adaptive landscapes through which pathways to nearly every genotype are available. Ultimately this may increase the diversity of genotypes in microbial populations.

  11. Hydrologic landscape units and adaptive management of intermountain wetlands

    USGS Publications Warehouse

    Custer, Stephen G.; Sojda, R.S.

    2006-01-01

    daptive management is often proposed to assist in the management of national wildlife refuges and allows the exploration of alternatives as well as the addition of ne w knowledge as it becomes available. The hydrological landscape unit can be a good foundation for such efforts. Red Rock Lakes National Wildlife Refuge (NWR) is in an intermountain basin dominated by vertical tectonics in the Northern Rocky Mountains. A geographic information system was used to define the boundaries for the hydrologic landscape units there. Units identified include alluvial fan, interfan, stream alluvi um and basin flat. Management alternatives can be informed by ex amination of processes that occu r on the units. For example, an ancient alluvial fan unit related to Red Rock Creek appear s to be isolated from stream flow today, with recharge dominated by precipitation and bedrock springs; while other alluvial fan units in the area have shallow ground water recharged from mountain streams and precipitation. The scale of hydrologic processes in interfan units differs from that in alluvial fan hydrologic landscape units. These differences are important when the refuge is evaluating habitat management activities. Hydrologic landscape units provide scientific unde rpinnings for the refuge’s comprehensive planning process. New geologic, hydrologic, and biologic knowledge can be integrated into the hydrologic landscape unit definition and improve adaptive management.

  12. IMPACTS OF PATCH SIZE AND LANDSCAPE HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

    EPA Science Inventory

    Impacts of Patch Size and Landscape Heterogeneity on Thematic Image Classification Accuracy.
    Currently, most thematic accuracy assessments of classified remotely sensed images oily account for errors between the various classes employed, at particular pixels of interest, thu...

  13. Adaptation in protein fitness landscapes is facilitated by indirect paths

    PubMed Central

    Wu, Nicholas C; Dai, Lei; Olson, C Anders; Lloyd-Smith, James O; Sun, Ren

    2016-01-01

    The structure of fitness landscapes is critical for understanding adaptive protein evolution. Previous empirical studies on fitness landscapes were confined to either the neighborhood around the wild type sequence, involving mostly single and double mutants, or a combinatorially complete subgraph involving only two amino acids at each site. In reality, the dimensionality of protein sequence space is higher (20L) and there may be higher-order interactions among more than two sites. Here we experimentally characterized the fitness landscape of four sites in protein GB1, containing 204 = 160,000 variants. We found that while reciprocal sign epistasis blocked many direct paths of adaptation, such evolutionary traps could be circumvented by indirect paths through genotype space involving gain and subsequent loss of mutations. These indirect paths alleviate the constraint on adaptive protein evolution, suggesting that the heretofore neglected dimensions of sequence space may change our views on how proteins evolve. DOI: http://dx.doi.org/10.7554/eLife.16965.001 PMID:27391790

  14. Hydrologic landscape classification evaluates streamflow vulnerability to climate change in Oregon, USA

    EPA Science Inventory

    Classification can allow assessments of the hydrologic functions of landscapes and their responses to stressors. Here we demonstrate the use of a hydrologic landscape (HL) approach to assess vulnerability to potential future climate change at statewide and basin scales. The HL ...

  15. Use of hydrologic landscape classification to diagnose streamflow predictability in Oregon

    EPA Science Inventory

    We implement a spatially lumped rainfall-runoff model to predict daily streamflow at 88 catchments within Oregon, USA and analyze its performance within the context of Oregon Hydrologic Landscapes (OHL) classification. OHL classification is used to characterize the physio-climat...

  16. Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

    PubMed Central

    Moran, Emilio Federico.

    2010-01-01

    High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

  17. Prospects for hydrologic classification of landscapes and watersheds

    EPA Science Inventory

    The ecological functions of streams and associated riparian zones are strongly influenced by the hydrological attributes of watersheds and landscapes in which they occur. Oregon hydrologic landscape regions (HLRs) have been defined based on four types of GIS data: 1) climate, 2) ...

  18. PATTERN RECOGNITION AND CLASSIFICATION USING ADAPTIVE LINEAR NEURON DEVICES

    DTIC Science & Technology

    adaption by an adaptive linear neuron ( Adaline ), as applied to the pattern recognition and classification problem; (2) Four possible iterative adaption...schemes which may be used to train as Adaline ; (3) Use of Multiple Adalines (Madaline) and two logic layers to increase system capability; and (4) Use...of Adaline in the practical fields of Speech Recognition, Weather Forecasting and Adaptive Control Systems and the possible use of Madaline in the Character Recognition field.

  19. Mapping agricultural landscapes and characterizing adaptive capacity in Central America

    NASA Astrophysics Data System (ADS)

    Holland, M. B.; Imbach, P. A.; Bouroncle, C.; Donatti, C.; Leguia, E.; Martinez, M.; Medellin, C.; Saborio-Rodriguez, M.; Shamer, S.; Zamora, J.

    2013-12-01

    One of the key challenges in developing adaptation strategies for smallholder farmers in developing countries is that of a data-poor environment, where spatially-explicit information about where the most vulnerable smallholder communities are located is lacking. Developing countries tend to lack consistent and reliable maps on agricultural land use, and have limited information available on smallholder adaptive capacity. We developed a novel participatory and expert mapping process to overcome these barriers and develop detailed national-scale maps that allow for a characterization of unique agricultural landscapes based on profiles of adaptive capacity for smallholder agriculture in each area. This research focuses specifically on the Central American nations of Costa Rica, Guatemala, and Honduras, where our focus is on coffee and basic grains as the two main cropping systems. Here we present the methodology and results of a series of in-depth interviews and participatory mapping sessions with experts working within the broader agricultural sector in each country. We held individual interviews and mapping sessions with approximately thirty experts from each country, and used a detailed survey instrument for each mapping session to both spatially identify distinct agricultural landscapes, and to further characterize each area based on specific farm practices and social context. The survey also included a series of questions to help us assess the relative adaptive capacity of smallholder agriculture within each landscape. After all expert mapping sessions were completed in each country we convened an expert group to assist in both validating and refining the set of landscapes already defined. We developed a characterization of adaptive capacity by aggregating indicators into main assets-based criteria (e.g. land tenure, access to credit, access to technical assistance, sustainable farm practices) derived from further expert weighting of indicators through an online

  20. Application of Unsupervised Clustering using Sparse Representations on Learned Dictionaries to develop Land Cover Classifications in Arctic Landscapes

    NASA Astrophysics Data System (ADS)

    Rowland, J. C.; Moody, D. I.; Brumby, S.; Gangodagamage, C.

    2012-12-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. Successful application of novel unsupervised feature extraction and clustering algorithms for use in Land Cover Classification requires the ability to determine what landscape attributes are represented by automated clustering. A closely related challenge is learning how to precondition the input data streams to the unsupervised classification algorithms in order to obtain clusters that represent Land Cover category of relevance to landsurface change and modeling applications. We present results from an ongoing effort to apply novel clustering methodologies developed primarily for neuroscience machine vision applications to the environmental sciences. We use a Hebbian learning rule to build spectral-textural dictionaries that are adapted to the data. We learn our dictionaries from millions of overlapping image patches and then use a pursuit search to generate sparse classification features. These sparse representations of pixel patches are used to perform unsupervised k-means clustering. In our application, we use 8-band multispectral Worldview-2 data from three arctic study areas: Barrow, Alaska; the Selawik River, Alaska; and a watershed near the Mackenzie River delta in northwest Canada. Our goal is to develop a robust classification methodology that will allow for the automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g. soil moisture and inundation), and topographic/geomorphic characteristics. The challenge of developing a meaningful land cover classification includes both learning how optimize the clustering algorithm and successfully interpreting the results. In applying the unsupervised clustering, we have the flexibility of selecting both the window

  1. Host coevolution alters the adaptive landscape of a virus

    PubMed Central

    2016-01-01

    The origin of new and complex structures and functions is fundamental for shaping the diversity of life. Such key innovations are rare because they require multiple interacting changes. We sought to understand how the adaptive landscape led to an innovation whereby bacteriophage λ evolved the new ability to exploit a receptor, OmpF, on Escherichia coli cells. Previous work showed that this ability evolved repeatedly, despite requiring four mutations in one virus gene. Here, we examine how this innovation evolved by studying six intermediate genotypes of λ isolated during independent transitions to exploit OmpF and comparing them to their ancestor. All six intermediates showed large increases in their adsorption rates on the ancestral host. Improvements in adsorption were offset, in large part, by the evolution of host resistance, which occurred by reduced expression of LamB, the usual receptor for λ. As a consequence of host coevolution, the adaptive landscape of the virus changed such that selection favouring four of the six virus intermediates became stronger after the host evolved resistance, thereby accelerating virus populations along the path to using the new OmpF receptor. This dependency of viral fitness on host genotype thus shows an important role for coevolution in the origin of the new viral function. PMID:27683370

  2. The Landscape of long non-coding RNA classification

    PubMed Central

    St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

    2015-01-01

    Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

  3. Oregon Hydrologic Landscapes: An Approach for Broadscale Hydrologic Classification

    EPA Science Inventory

    Gaged streams represent only a small percentage of watershed hydrologic conditions throughout the Unites States and globe, but there is a growing need for hydrologic classification systems that can serve as the foundation for broad-scale assessments of the hydrologic functions of...

  4. Landscape genetics, adaptive diversity and population structure in Phaseolus vulgaris.

    PubMed

    Rodriguez, Monica; Rau, Domenico; Bitocchi, Elena; Bellucci, Elisa; Biagetti, Eleonora; Carboni, Andrea; Gepts, Paul; Nanni, Laura; Papa, Roberto; Attene, Giovanna

    2016-03-01

    Here we studied the organization of genetic variation of the common bean (Phaseolus vulgaris) in its centres of domestication. We used 131 single nucleotide polymorphisms to investigate 417 wild common bean accessions and a representative sample of 160 domesticated genotypes, including Mesoamerican and Andean genotypes, for a total of 577 accessions. By analysing the genetic spatial patterns of the wild common bean, we documented the existence of several genetic groups and the occurrence of variable degrees of diversity in Mesoamerica and the Andes. Moreover, using a landscape genetics approach, we demonstrated that both demographic processes and selection for adaptation were responsible for the observed genetic structure. We showed that the study of correlations between markers and ecological variables at a continental scale can help in identifying local adaptation genes. We also located putative areas of common bean domestication in Mesoamerica, in the Oaxaca Valley, and the Andes, in southern Bolivia-northern Argentina. These observations are of paramount importance for the conservation and exploitation of the genetic diversity preserved within this species and other plant genetic resources.

  5. Classification of adaptive memetic algorithms: a comparative study.

    PubMed

    Ong, Yew-Soon; Lim, Meng-Hiot; Zhu, Ning; Wong, Kok-Wai

    2006-02-01

    Adaptation of parameters and operators represents one of the recent most important and promising areas of research in evolutionary computations; it is a form of designing self-configuring algorithms that acclimatize to suit the problem in hand. Here, our interests are on a recent breed of hybrid evolutionary algorithms typically known as adaptive memetic algorithms (MAs). One unique feature of adaptive MAs is the choice of local search methods or memes and recent studies have shown that this choice significantly affects the performances of problem searches. In this paper, we present a classification of memes adaptation in adaptive MAs on the basis of the mechanism used and the level of historical knowledge on the memes employed. Then the asymptotic convergence properties of the adaptive MAs considered are analyzed according to the classification. Subsequently, empirical studies on representatives of adaptive MAs for different type-level meme adaptations using continuous benchmark problems indicate that global-level adaptive MAs exhibit better search performances. Finally we conclude with some promising research directions in the area.

  6. Mutual Information Item Selection in Adaptive Classification Testing

    ERIC Educational Resources Information Center

    Weissman, Alexander

    2007-01-01

    A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local-…

  7. Adaptive stellar spectral subclass classification based on Bayesian SVMs

    NASA Astrophysics Data System (ADS)

    Du, Changde; Luo, Ali; Yang, Haifeng

    2017-02-01

    Stellar spectral classification is one of the most fundamental tasks in survey astronomy. Many automated classification methods have been applied to spectral data. However, their main limitation is that the model parameters must be tuned repeatedly to deal with different data sets. In this paper, we utilize the Bayesian support vector machines (BSVM) to classify the spectral subclass data. Based on Gibbs sampling, BSVM can infer all model parameters adaptively according to different data sets, which allows us to circumvent the time-consuming cross validation for penalty parameter. We explored different normalization methods for stellar spectral data, and the best one has been suggested in this study. Finally, experimental results on several stellar spectral subclass classification problems show that the BSVM model not only possesses good adaptability but also provides better prediction performance than traditional methods.

  8. An operational framework for object-based land use classification of heterogeneous rural landscapes

    NASA Astrophysics Data System (ADS)

    Watmough, Gary R.; Palm, Cheryl A.; Sullivan, Clare

    2017-02-01

    The characteristics of very high resolution (VHR) satellite data are encouraging development agencies to investigate its use in monitoring and evaluation programmes. VHR data pose challenges for land use classification of heterogeneous rural landscapes as it is not possible to develop generalised and transferable land use classification definitions and algorithms. We present an operational framework for classifying VHR satellite data in heterogeneous rural landscapes using an object-based and random forest classifier. The framework overcomes the challenges of classifying VHR data in anthropogenic landscapes. It does this by using an image stack of RGB-NIR, Normalised Difference Vegetation Index (NDVI) and textural bands in a two-phase object-based classification. The framework can be applied to data acquired by different sensors, with different view and illumination geometries, at different times of the year. Even with these complex input data the framework can produce classification results that are comparable across time. Here we describe the framework and present an example of its application using data from QuickBird (2 images) and GeoEye (1 image) sensors.

  9. Extreme learning machine and adaptive sparse representation for image classification.

    PubMed

    Cao, Jiuwen; Zhang, Kai; Luo, Minxia; Yin, Chun; Lai, Xiaoping

    2016-09-01

    Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks, e.g., in general, ELM is known to be less robust to noise while SRC is known to be time-consuming. Consequently, ELM and SRC complement each other in computational complexity and classification accuracy. In order to unify such mutual complementarity and thus further enhance the classification performance, we propose an efficient hybrid classifier to exploit the advantages of ELM and SRC in this paper. More precisely, the proposed classifier consists of two stages: first, an ELM network is trained by supervised learning. Second, a discriminative criterion about the reliability of the obtained ELM output is adopted to decide whether the query image can be correctly classified or not. If the output is reliable, the classification will be performed by ELM; otherwise the query image will be fed to SRC. Meanwhile, in the stage of SRC, a sub-dictionary that is adaptive to the query image instead of the entire dictionary is extracted via the ELM output. The computational burden of SRC thus can be reduced. Extensive experiments on handwritten digit classification, landmark recognition and face recognition demonstrate that the proposed hybrid classifier outperforms ELM and SRC in classification accuracy with outstanding computational efficiency.

  10. Adaptive color correction based on object color classification

    NASA Astrophysics Data System (ADS)

    Kotera, Hiroaki; Morimoto, Tetsuro; Yasue, Nobuyuki; Saito, Ryoichi

    1998-09-01

    An adaptive color management strategy depending on the image contents is proposed. Pictorial color image is classified into different object areas with clustered color distribution. Euclidian or Mahalanobis color distance measures, and maximum likelihood method based on Bayesian decision rule, are introduced to the classification. After the classification process, each clustered pixels are projected onto principal component space by Hotelling transform and the color corrections are performed for the principal components to be matched each other in between the individual clustered color areas of original and printed images.

  11. Classification of pasture habitats by Hungarian herders in a steppe landscape (Hungary)

    PubMed Central

    2012-01-01

    Background Landscape ethnoecology focuses on the ecological features of the landscape, how the landscape is perceived, and used by people who live in it. Though studying folk classifications of species has a long history, the comparative study of habitat classifications is just beginning. I studied the habitat classification of herders in a Hungarian steppe, and compared it to classifications of botanists and laymen. Methods For a quantitative analysis the picture sort method was used. Twenty-three pictures of 7-11 habitat types were sorted by 25 herders.’Density’ of pictures along the habitat gradient of the Hortobágy salt steppe was set as equal as possible, but pictures differed in their dominant species, wetness, season, etc. Before sorts, herders were asked to describe pictures to assure proper recognition of habitats. Results Herders classified the images into three main groups: (1) fertile habitats at the higher parts of the habitat gradient (partos, lit. on the shore); (2) saline habitats (szík, lit. salt or saline place), and (3) meadows and marshes (lapos, lit. flooded) at the lower end of the habitat gradient. Sharpness of delimitation changed along the gradient. Saline habitats were the most isolated from the rest. Botanists identified 6 groups. Laymen grouped habitats in a less coherent way. As opposed to my expectations, botanical classification was not more structured than that done by herders. I expected and found high correspondence between the classifications by herders, botanists and laymen. All tended to recognize similar main groups: wetlands, ”good grass” and dry/saline habitats. Two main factors could have been responsible for similar classifications: salient features correlated (e.g. salinity recognizable by herders and botanists but not by laymen correlated with the density of grasslands or height of vegetation recognizable also for laymen), or the same salient features were used as a basis for sorting (wetness, and abiotic stress

  12. Undercomplete learned dictionaries for land cover classification in multispectral imagery of Arctic landscapes using CoSA: clustering of sparse approximations

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Gangodagamage, Chandana

    2013-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a Hebbian learning rule to build undercomplete spectral-textural dictionaries that are adapted to the data. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using our CoSA algorithm: unsupervised Clustering of Sparse Approximations. We demonstrate our method using multispectral Worldview-2 data from three Arctic study areas: Barrow, Alaska; the Selawik River, Alaska; and a watershed near the Mackenzie River delta in northwest Canada. Our goal is to develop a robust classification methodology that will allow for the automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and geomorphic characteristics. To interpret and assign land cover categories to the clusters we both evaluate the spectral properties of the clusters and compare the clusters to both field- and remote sensing-derived classifications of landscape attributes. Our work suggests that neuroscience-based models are a promising approach to practical pattern recognition problems in remote sensing.

  13. Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

    PubMed Central

    Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

    2015-01-01

    Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape

  14. Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

    PubMed

    Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

    2015-01-01

    Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape

  15. Implementation of Multispectral Image Classification on a Remote Adaptive Computer

    NASA Technical Reports Server (NTRS)

    Figueiredo, Marco A.; Gloster, Clay S.; Stephens, Mark; Graves, Corey A.; Nakkar, Mouna

    1999-01-01

    As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

  16. Community participatory landscape classification and biodiversity assessment and monitoring of grazing lands in northern Kenya.

    PubMed

    Roba, Hassan G; Oba, Gufu

    2009-02-01

    In this study, we asked the Ariaal herders of northern Kenya to answer "why, what and how" they classified landscape, and assessed and monitored the biodiversity of 10 km(2) of grazing land. To answer the "why question" the herders classified grazing resources into 39 landscape patches grouped into six landscape types and classified soil as 'warm', 'intermediate' or 'cold' for the purpose of land use. For the "what question" the herders used soil conditions and vegetation characteristics to assess biodiversity. Plant species were described as 'increasers', 'decreasers' or 'stable'. The decreaser species were mostly grasses and forbs preferred for cattle and sheep grazing and the increasers were mostly woody species preferred by goats. The herders evaluated biodiversity in terms of key forage species and used absence or presence of the preferred species from individual landscapes for monitoring change in biodiversity. For the "how question" the herders used anthropogenic indicators concerned with livestock management for assessing landscape potential and suitability for grazing. The anthropogenic indicators were related to soils and biodiversity. The herders used plant species grazing preferences to determine the links between livestock production and biodiversity. By addressing these three questions, the study shows the value of incorporating the indigenous knowledge of herders into classification of landscape and assessment and monitoring of biodiversity in the grazing lands. We conclude that herder knowledge of biodiversity is related to the use as opposed to exclusive conservation practices. This type of knowledge is extremely valuable to conservation agencies for establishing a baseline for monitoring changes in biodiversity in the future.

  17. Landscape Risk Factors for Lyme Disease in the Eastern Broadleaf Forest Province of the Hudson River Valley and the Effect of Explanatory Data Classification Resolution

    EPA Science Inventory

    This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity)...

  18. Polytomous Adaptive Classification Testing: Effects of Item Pool Size, Test Termination Criterion, and Number of Cutscores

    ERIC Educational Resources Information Center

    Gnambs, Timo; Batinic, Bernad

    2011-01-01

    Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification…

  19. Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.

    PubMed

    Park, Juyoung; Kang, Mingon; Gao, Jean; Kim, Younghoon; Kang, Kyungtae

    2017-01-01

    Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.

  20. Achieving effective landscape conservation: evolving demands adaptive metrics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rapid changes in demographics and on- and off-farm land use limit the impacts of U.S. conservation programs and present particular challenges to future conservation efforts. The fragmentation of landscape through urban, suburban, and peri-urban development, coincident with demographic shifts, has s...

  1. Fanning - A classification algorithm for mixture landscapes applied to Landsat data of Maine forests

    NASA Technical Reports Server (NTRS)

    Ungar, S. G.; Bryant, E.

    1981-01-01

    It is pointed out that typical landscapes include a relatively small number of 'pure' land cover types which combine in various proportions to form a myriad of mixture types. Most Landsat classifications algorithms used today require a separate user specification for each category, including mixture categories. Attention is given to a simpler approach, which would require the user to specify only the 'pure' types. Mixture pixels would be classified on the basis of the proportion of the area covered by each pure type within the pixel. The 'fanning' algorithm quantifies varying proportions of two 'pure' land cover types in selected mixture pixels. This algorithm was applied to 200,000 ha of forest land in Maine, taking into account a comparison with standard inventory information. Results compared well with a discrete categories classification of the same area.

  2. Classification of vegetation in an open landscape using full-waveform airborne laser scanner data

    NASA Astrophysics Data System (ADS)

    Alexander, Cici; Deák, Balázs; Kania, Adam; Mücke, Werner; Heilmeier, Hermann

    2015-09-01

    Airborne laser scanning (ALS) is increasingly being used for the mapping of vegetation, although the focus so far has been on woody vegetation, and ALS data have only rarely been used for the classification of grassland vegetation. In this study, we classified the vegetation of an open alkali landscape, characterized by two Natura 2000 habitat types: Pannonic salt steppes and salt marshes and Pannonic loess steppic grasslands. We generated 18 variables from an ALS dataset collected in the growing (leaf-on) season. Elevation is a key factor determining the patterns of vegetation types in the landscape, and hence 3 additional variables were based on a digital terrain model (DTM) generated from an ALS dataset collected in the dormant (leaf-off) season. We classified the vegetation into 24 classes based on these 21 variables, at a pixel size of 1 m. Two groups of variables with and without the DTM-based variables were used in a Random Forest classifier, to estimate the influence of elevation, on the accuracy of the classification. The resulting classes at Level 4, based on associations, were aggregated at three levels - Level 3 (11 classes), Level 2 (8 classes) and Level 1 (5 classes) - based on species pool, site conditions and structure, and the accuracies were assessed. The classes were also aggregated based on Natura 2000 habitat types to assess the accuracy of the classification, and its usefulness for the monitoring of habitat quality. The vegetation could be classified into dry grasslands, wetlands, weeds, woody species and man-made features, at Level 1, with an accuracy of 0.79 (Cohen's kappa coefficient, κ). The accuracies at Levels 2-4 and the classification based on the Natura 2000 habitat types were κ: 0.76, 0.61, 0.51 and 0.69, respectively. Levels 1 and 2 provide suitable information for nature conservationists and land managers, while Levels 3 and 4 are especially useful for ecologists, geologists and soil scientists as they provide high resolution

  3. Visions of Restoration in Fire-Adapted Forest Landscapes: Lessons from the Collaborative Forest Landscape Restoration Program

    NASA Astrophysics Data System (ADS)

    Urgenson, Lauren S.; Ryan, Clare M.; Halpern, Charles B.; Bakker, Jonathan D.; Belote, R. Travis; Franklin, Jerry F.; Haugo, Ryan D.; Nelson, Cara R.; Waltz, Amy E. M.

    2017-02-01

    Collaborative approaches to natural resource management are becoming increasingly common on public lands. Negotiating a shared vision for desired conditions is a fundamental task of collaboration and serves as a foundation for developing management objectives and monitoring strategies. We explore the complex socio-ecological processes involved in developing a shared vision for collaborative restoration of fire-adapted forest landscapes. To understand participant perspectives and experiences, we analyzed interviews with 86 respondents from six collaboratives in the western U.S., part of the Collaborative Forest Landscape Restoration Program established to encourage collaborative, science-based restoration on U.S. Forest Service lands. Although forest landscapes and group characteristics vary considerably, collaboratives faced common challenges to developing a shared vision for desired conditions. Three broad categories of challenges emerged: meeting multiple objectives, collaborative capacity and trust, and integrating ecological science and social values in decision-making. Collaborative groups also used common strategies to address these challenges, including some that addressed multiple challenges. These included use of issue-based recommendations, field visits, and landscape-level analysis; obtaining support from local agency leadership, engaging facilitators, and working in smaller groups (sub-groups); and science engagement. Increased understanding of the challenges to, and strategies for, developing a shared vision of desired conditions is critical if other collaboratives are to learn from these efforts.

  4. Transforming landscape ecological evaluations using sub-pixel remote sensing classifications: A study of invasive saltcedar (Tamarix spp.)

    NASA Astrophysics Data System (ADS)

    Frazier, Amy E.

    Invasive species disrupt landscape patterns and compromise the functionality of ecosystem processes. Non-native saltcedar (Tamarix spp.) poses significant threats to native vegetation and groundwater resources in the southwestern U.S. and Mexico, and quantifying spatial and temporal distribution patterns is essential for monitoring its spread. Advanced remote sensing classification techniques such as sub-pixel classifications are able to detect and discriminate saltcedar from native vegetation with high accuracy, but these types of classifications are not compatible with landscape metrics, which are the primary tool available for statistically assessing distribution patterns, because they do not have discrete class boundaries. The objective of this research is to develop new methods that allow sub-pixel classifications to be analyzed using landscape metrics. The research will be carried out through three specific aims: (1) develop and test a method to transform continuous sub-pixel classifications into categorical representations that are compatible with widely used landscape metric tools, (2) establish a gradient-based concept of landscape using sub-pixel classifications and the technique developed in the first objective to explore the relationships between pattern and process, and (3) generate a new super-resolution mapping technique method to predict the spatial locations of fractional land covers within a pixel. Results show that the threshold gradient method is appropriate for discretizing sub-pixel data, and can be used to generate increased information about the landscape compared to traditional single-value metrics. Additionally, the super-resolution classification technique was also able to provide detailed sub-pixel mapping information, but additional work will be needed to develop rigorous validation and accuracy assessment techniques.

  5. Autonomous underwater vehicle adaptive path planning for target classification

    NASA Astrophysics Data System (ADS)

    Edwards, Joseph R.; Schmidt, Henrik

    2002-11-01

    Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

  6. Convergent Evolution During Local Adaptation to Patchy Landscapes

    PubMed Central

    2015-01-01

    Species often encounter, and adapt to, many patches of similar environmental conditions across their range. Such adaptation can occur through convergent evolution if different alleles arise in different patches, or through the spread of shared alleles by migration acting to synchronize adaptation across the species. The tension between the two reflects the constraint imposed on evolution by the underlying genetic architecture versus how effectively selection and geographic isolation act to inhibit the geographic spread of locally adapted alleles. This paper studies the balance between these two routes to adaptation in a model of continuous environments with patchy selection pressures. We address the following questions: How long does it take for a novel allele to appear in a patch where it is locally adapted through mutation? Or, through migration from another, already adapted patch? Which is more likely to occur, as a function of distance between the patches? What population genetic signal is left by the spread of migrant alleles? To answer these questions we examine the family structure underlying migration–selection equilibrium surrounding an already adapted patch, treating those rare families that reach new patches as spatial branching processes. A main result is that patches further apart than a critical distance will likely evolve independent locally adapted alleles; this distance is proportional to the spatial scale of selection (σ/sm, where σ is the dispersal distance and s m is the selective disadvantage of these alleles between patches), and depends linearly on log(s m/μ), where μ is the mutation rate. This provides a way to understand the role of geographic separation between patches in promoting convergent adaptation and the genomic signals it leaves behind. We illustrate these ideas using the convergent evolution of cryptic coloration in the rock pocket mouse, Chaetodipus intermedius, as an empirical example. PMID:26571125

  7. Spatial variation, mapping, and classification of moss families in semi-arid landscapes in NW Turkey.

    PubMed

    Abay, Gökhan; Gül, Ebru; Günlü, Alkan; Erşahin, Sabit; Ursavaş, Serhat

    2015-03-01

    Geostatistics and remote sensing techniques are frequently used in analyzing the spatial variability of terrestrial ecosystems. We analyzed spatial variation of moss families by geostatistics and Landsat imagery in a typical semi-arid landscape in North Central Anatolia, Turkey. We sampled 49 sites, chosen based on elevation, slope steepness, and slope aspect. Moss families were determined in a 10-m(2) representative area at each sampling site. The samples were transported to a laboratory and identified for moss families. In total, 10 families were found. Semivariogram analysis was performed to analyze the spatial structure of these families. The semivariogram analysis showed that the moss families were spatially dependent within 117 m in the study area. Thirteen thematic classes were categorized by Landsat Thematic Mapper (TM) image in the study area. The classification resulted in an overall kappa statistic of 0.8535, producer accuracy of 74.29, and user accuracy of 86.67. The family with the lowest classification accuracy was Orthotrichaceae (kappa of 0.6379, producer accuracy of 64.52, and user accuracy of 66.67). The moss families and the other classes were identified with a 0.78 kappa statistic value and an 80.74 % accuracy level by using the Landsat TM. The classification showed that Brachytheciaceae, Pottiaceae, Bryaceae, and Grimmiaceae were the most abundant moss families in this semi-arid environment.

  8. Structured estimation - Sample size reduction for adaptive pattern classification

    NASA Technical Reports Server (NTRS)

    Morgera, S.; Cooper, D. B.

    1977-01-01

    The Gaussian two-category classification problem with known category mean value vectors and identical but unknown category covariance matrices is considered. The weight vector depends on the unknown common covariance matrix, so the procedure is to estimate the covariance matrix in order to obtain an estimate of the optimum weight vector. The measure of performance for the adapted classifier is the output signal-to-interference noise ratio (SIR). A simple approximation for the expected SIR is gained by using the general sample covariance matrix estimator; this performance is both signal and true covariance matrix independent. An approximation is also found for the expected SIR obtained by using a Toeplitz form covariance matrix estimator; this performance is found to be dependent on both the signal and the true covariance matrix.

  9. Adaptive evolutionary artificial neural networks for pattern classification.

    PubMed

    Oong, Tatt Hee; Isa, Nor Ashidi Mat

    2011-11-01

    This paper presents a new evolutionary approach called the hybrid evolutionary artificial neural network (HEANN) for simultaneously evolving an artificial neural networks (ANNs) topology and weights. Evolutionary algorithms (EAs) with strong global search capabilities are likely to provide the most promising region. However, they are less efficient in fine-tuning the search space locally. HEANN emphasizes the balancing of the global search and local search for the evolutionary process by adapting the mutation probability and the step size of the weight perturbation. This is distinguishable from most previous studies that incorporate EA to search for network topology and gradient learning for weight updating. Four benchmark functions were used to test the evolutionary framework of HEANN. In addition, HEANN was tested on seven classification benchmark problems from the UCI machine learning repository. Experimental results show the superior performance of HEANN in fine-tuning the network complexity within a small number of generations while preserving the generalization capability compared with other algorithms.

  10. Cherokee Adaptation to the Landscape of the West and Overcoming the Loss of Culturally Significant Plants

    ERIC Educational Resources Information Center

    Vick, R. Alfred

    2011-01-01

    Plant species utilized by Cherokees have been documented by several authors. However, many of the traditional uses of plants were lost or forgotten in the generations following the Trail of Tears. The pressures of overcoming the physical and psychological impact of the removal, adapting to a new landscape, rebuilding a government, rebuilding…

  11. An Interactive Computer Program to Construct Adaptive Landscapes and to Simulate the Changes Expected with Selection

    ERIC Educational Resources Information Center

    Hull, Peter

    1978-01-01

    Describes an interactive computer program which can be used by students to construct adaptive landscapes of two types as an illustration of the expected effects of selection. Simulates effects of selection on populations of this type and changes of gene frequency can be plotted on the same contour map. (Author/MA)

  12. Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model

    PubMed Central

    Neidhart, Johannes; Szendro, Ivan G.; Krug, Joachim

    2014-01-01

    Much of the current theory of adaptation is based on Gillespie’s mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. PMID:25123507

  13. [Ecological classification system of forest landscape in eastern mountainous region of Liaoning Province].

    PubMed

    Tang, Li-na; Wang, Qing-li; Dai, Li-min; Shao, Guo-fan

    2008-01-01

    Based on Digital Elevation Models (DEM) and satellite SPOT-5 data, and by using the spatial analysis function in Geographic Information System, a hierachical Ecological Classification System of forest landscape was developed for the eastern mountainous region of Liaoning Province, and the two lowest layers in the hierachical framework, Ecological Land Types (ELTs) and Ecological Land Type Phases (ELTPs), were mapped. The results indicated that there were 5 ELTs and 34 ELTPs. The boundaries of ELTs, which presented the potential vegetation distribution and potential forestry ecosystem productivity, were determined by environmental conditions quantified by DEM. ELTPs were classified by overlaying ELTs with forest vegetation data layers which were obtained from remotely sensed data, forest inventory data, and ground data. The ELTPs represented the divisions of land in terms of both natural and human-induced forest conditions, and therefore, were reliable units for forest inventories and management. ELTPs could function as conventional forest inventory sub-compartments. By this means, forestry departments could adjust forest management planning and forest management measures from the viewpoint of forest landscape scale to realize forest ecosystem management.

  14. Analysis of adaptive walks on NK fitness landscapes with different interaction schemes

    NASA Astrophysics Data System (ADS)

    Nowak, Stefan; Krug, Joachim

    2015-06-01

    Fitness landscapes are genotype to fitness mappings commonly used in evolutionary biology and computer science which are closely related to spin glass models. In this paper, we study the NK model for fitness landscapes where the interaction scheme between genes can be explicitly defined. The focus is on how this scheme influences the overall shape of the landscape. Our main tool for the analysis are adaptive walks, an idealized dynamics by which the population moves uphill in fitness and terminates at a local fitness maximum. We use three different types of walks and investigate how their length (the number of steps required to reach a local peak) and height (the fitness at the endpoint of the walk) depend on the dimensionality and structure of the landscape. We find that the distribution of local maxima over the landscape is particularly sensitive to the choice of interaction pattern. Most quantities that we measure are simply correlated to the rank of the scheme, which is equal to the number of nonzero coefficients in the expansion of the fitness landscape in terms of Walsh functions.

  15. The adapting healer: pioneering through shifting epidemiological and sociocultural landscapes.

    PubMed

    McMillen, Heather

    2004-09-01

    While it is true that healers selectively adopt and/or refashion aspects of biomedicine, the influence is not unidirectional with information flowing exclusively from hospitals into the workplaces of healers. This article examines healers in Tanga, Tanzania to explore the reciprocal relations between practitioners of indigenous medicine and biomedicine. An abbreviated ethnography of one healer in coastal Tanzania is used to illustrate some of the relevant influences and possible adaptations of contemporary healers. His experiences illuminate how multiple factors, especially sociocultural changes, biomedicine, AIDS, and related research(ers) can influence healers' adaptations. In his case, biomedical health workers from a non-profit HIV organization call upon him not only to act as a liaison between their services and the community, but more importantly, to provide treatment for opportunistic infections and counseling for patients and to participate in biomedical and scientific projects. Reflecting on his experiences as a healer who has negotiated a position that straddles the world of biomedicine and the world of healers facilitates examination of important issues affecting healers today, including their relationship to biomedical health workers, bioprospectors, governments, non-profit organizations, and professional organizations of healers. Although the healer featured in this article is a pioneer in his own town, there are other examples in Africa where healers and biomedical practitioners are interacting. Therefore, he may represent a trend in healer adaptation.

  16. Adaptation and Coevolution on an Emergent Global Competitive Landscape

    NASA Astrophysics Data System (ADS)

    Fellman, Philip Vos; Post, Jonathan Vos; Wright, Roxana; Dasari, Usha

    Notions of Darwinian selection have been implicit in economic theory for at least sixty years. Richard Nelson and Sidney Winter have argued that while evolutionary thinking was prevalent in prewar economics, the postwar Neoclassical school became almost entirely preoccupied with equilibrium conditions and their mathematical conditions. One of the problems with the economic interpretation of firm selection through competition has been a weak grasp on an incomplete scientific paradigm. As I.F. Price notes: "The biological metaphor has long lurked in the background of management theory largely because the message of 'survival of the fittest' (usually wrongly attributed to Charles Darwin rather than Herbert Spencer) provides a seemingly natural model for market competition (e.g. Alchian 1950, Merrell 1984, Henderson 1989, Moore 1993), without seriously challenging the underlying paradigms of what an organisation is." [1] In this paper we examine the application of dynamic fitness landscape models to economic theory, particularly the theory of technology substitution, drawing on recent work by Kauffman, Arthur, McKelvey, Nelson and Winter, and Windrum and Birchenhall. In particular we use Professor Post's early work with John Holland on the genetic algorithm to explain some of the key differences between static and dynamic approaches to economic modeling.

  17. Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

    PubMed Central

    Beare, Richard J.; Chen, Jian; Kelly, Claire E.; Alexopoulos, Dimitrios; Smyser, Christopher D.; Rogers, Cynthia E.; Loh, Wai Y.; Matthews, Lillian G.; Cheong, Jeanie L. Y.; Spittle, Alicia J.; Anderson, Peter J.; Doyle, Lex W.; Inder, Terrie E.; Seal, Marc L.; Thompson, Deanne K.

    2016-01-01

    Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T2-weighted images of preterm infants (born <30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical gray

  18. Adaptation of Bird Communities to Farmland Abandonment in a Mountain Landscape

    PubMed Central

    Guilherme, João Lopes; Miguel Pereira, Henrique

    2013-01-01

    Widespread farmland abandonment has led to significant landscape transformations of many European mountain areas. These semi-natural multi-habitat landscapes are important reservoirs of biodiversity and their abandonment has important conservation implications. In multi-habitat landscapes the adaptation of communities depends on the differential affinity of the species to the available habitats. We use nested species-area relationships (SAR) to model species richness patterns of bird communities across scales in a mountain landscape, in NW Portugal. We compare the performance of the classic-SAR and the countryside-SAR (i.e. multi-habitat) models at the landscape scale, and compare species similarity decay (SSD) at the regional scale. We find a considerable overlap of bird communities in the different land-uses (farmland, shrubland and oak forest) at the landscape scale. Analysis of the classic and countryside SAR show that specialist species are strongly related to their favourite habitat. Farmland and shrubland have higher regional SSD compared to oak forests. However, this is due to the opportunistic use of farmlands by generalist birds. Forest specialists display significant regional turnover in oak forest. Overall, the countryside-SAR model had a better fit to the data showing that habitat composition determines species richness across scales. Finally, we use the countryside-SAR model to forecast bird diversity under four scenarios of land-use change. Farmland abandonment scenarios show little impact on bird diversity as the model predicts that the complete loss of farmland is less dramatic, in terms of species diversity loss, than the disappearance of native Galicio-Portuguese oak forest. The affinities of species to non-preferred habitats suggest that bird communities can adapt to land-use changes derived from farmland abandonment. Based on model predictions we argue that rewilding may be a suitable management option for many European mountain areas. PMID

  19. Adaptation of bird communities to farmland abandonment in a mountain landscape.

    PubMed

    Guilherme, João Lopes; Miguel Pereira, Henrique

    2013-01-01

    Widespread farmland abandonment has led to significant landscape transformations of many European mountain areas. These semi-natural multi-habitat landscapes are important reservoirs of biodiversity and their abandonment has important conservation implications. In multi-habitat landscapes the adaptation of communities depends on the differential affinity of the species to the available habitats. We use nested species-area relationships (SAR) to model species richness patterns of bird communities across scales in a mountain landscape, in NW Portugal. We compare the performance of the classic-SAR and the countryside-SAR (i.e. multi-habitat) models at the landscape scale, and compare species similarity decay (SSD) at the regional scale. We find a considerable overlap of bird communities in the different land-uses (farmland, shrubland and oak forest) at the landscape scale. Analysis of the classic and countryside SAR show that specialist species are strongly related to their favourite habitat. Farmland and shrubland have higher regional SSD compared to oak forests. However, this is due to the opportunistic use of farmlands by generalist birds. Forest specialists display significant regional turnover in oak forest. Overall, the countryside-SAR model had a better fit to the data showing that habitat composition determines species richness across scales. Finally, we use the countryside-SAR model to forecast bird diversity under four scenarios of land-use change. Farmland abandonment scenarios show little impact on bird diversity as the model predicts that the complete loss of farmland is less dramatic, in terms of species diversity loss, than the disappearance of native Galicio-Portuguese oak forest. The affinities of species to non-preferred habitats suggest that bird communities can adapt to land-use changes derived from farmland abandonment. Based on model predictions we argue that rewilding may be a suitable management option for many European mountain areas.

  20. Social and natural sciences differ in their research strategies, adapted to work for different knowledge landscapes.

    PubMed

    Jaffe, Klaus

    2014-01-01

    Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide.

  1. Social and Natural Sciences Differ in Their Research Strategies, Adapted to Work for Different Knowledge Landscapes

    PubMed Central

    Jaffe, Klaus

    2014-01-01

    Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide. PMID:25426723

  2. Adaptive Capacity in Tanzanian Maasailand: Changing strategies to cope with drought in fragmented landscapes

    PubMed Central

    Riosmena, Fernando

    2014-01-01

    This study examines the ways in which the adaptive capacity of households to climatic events varies within communities and is mediated by institutional and landscape changes. We present qualitative and quantitative data from two Maasai communities differentially exposed to the devastating drought of 2009 in Northern Tanzania. We show how rangeland fragmentation combined with the decoupling of institutions and landscapes are affecting pastoralists ability to cope with drought. Our data highlight that mobility remains a key coping mechanism for pastoralists to avoid cattle loss during a drought. However, mobility is now happening in new ways that require not only large amounts of money but new forms of knowledge and connections outside of customary reciprocity networks. Those least affected by the drought, in terms of cattle lost, were those with large herds who were able to sell some of their cattle and to pay for private access to pastures outside of Maasai areas. Drawing on an entitlements framework, we argue that the new coping mechanisms are not available to all, could be making some households more vulnerable to climate change, and reduce the adaptive capacity of the overall system as reciprocity networks and customary institutions are weakened. As such, we posit that adaptive capacity to climate change is uneven within and across communities, is scale-dependent, and is intimately tied to institutional and landscape changes. PMID:25400331

  3. Exploring indigenous landscape classification across different dimensions: a case study from the Bolivian Amazon

    PubMed Central

    Riu-Bosoms, Carles; Vidal-Amat, Teresa; Duane, Andrea; Fernandez-Llamazares, Alvaro; Guèze, Maximilien; Luz, Ana C.; Macía, Manuel J.; Paneque-Gálvez, Jaime; Reyes-García, Victoria

    2013-01-01

    Decisions on landscape management are often dictated by government officials based on their own understandings of how landscape should be used and managed, but rarely considering local peoples’ understandings of the landscape they inhabit. We use data collected through free listings, field transects, and interviews to describe how an Amazonian group of hunter-horticulturalists, the Tsimane’, classify and perceive the importance of different elements of the landscape across the ecological, socioeconomic, and spiritual dimensions. The Tsimane’ recognize nine folk ecotopes (i.e., culturally-recognized landscape units) and use a variety of criteria (including geomorphological features and landscape uses) to differentiate ecotopes from one another. The Tsimane’ rank different folk ecotopes in accordance with their perceived ecological, socioeconomic, and spiritual importance. Understanding how local people perceive their landscape contributes towards a landscape management planning paradigm that acknowledges the continuing contributions to management of landscape inhabitants, as well as their cultural and land use rights. PMID:25821282

  4. Multiple-factor classification of a human-modified forest landscape in the Hsuehshan Mountain Range, Taiwan.

    PubMed

    Berg, Kevan J; Icyeh, Lahuy; Lin, Yih-Ren; Janz, Arnold; Newmaster, Steven G

    2016-12-01

    Human actions drive landscape heterogeneity, yet most ecosystem classifications omit the role of human influence. This study explores land use history to inform a classification of forestland of the Tayal Mrqwang indigenous people of Taiwan. Our objectives were to determine the extent to which human action drives landscape heterogeneity. We used interviews, field sampling, and multivariate analysis to relate vegetation patterns to environmental gradients and human modification across 76 sites. We identified eleven forest classes. In total, around 70 % of plots were at lower elevations and had a history of shifting cultivation, terrace farming, and settlement that resulted in alder, laurel, oak, pine, and bamboo stands. Higher elevation mixed conifer forests were least disturbed. Arboriculture and selective harvesting were drivers of other conspicuous forest patterns. The findings show that past land uses play a key role in shaping forests, which is important to consider when setting targets to guide forest management.

  5. On-board multispectral classification study. Volume 2: Supplementary tasks. [adaptive control

    NASA Technical Reports Server (NTRS)

    Ewalt, D.

    1979-01-01

    The operational tasks of the onboard multispectral classification study were defined. These tasks include: sensing characteristics for future space applications; information adaptive systems architectural approaches; data set selection criteria; and onboard functional requirements for interfacing with global positioning satellites.

  6. Effects of Estimation Bias on Multiple-Category Classification with an IRT-Based Adaptive Classification Procedure

    ERIC Educational Resources Information Center

    Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R.

    2006-01-01

    The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…

  7. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

    PubMed

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-12-16

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

  8. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

    PubMed Central

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-01-01

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

  9. Diagnostic Classification Models and Multidimensional Adaptive Testing: A Commentary on Rupp and Templin

    ERIC Educational Resources Information Center

    Frey, Andreas; Carstensen, Claus H.

    2009-01-01

    On a general level, the objective of diagnostic classifications models (DCMs) lies in a classification of individuals regarding multiple latent skills. In this article, the authors show that this objective can be achieved by multidimensional adaptive testing (MAT) as well. The authors discuss whether or not the restricted applicability of DCMs can…

  10. Testing Adaptive Hypotheses of Convergence with Functional Landscapes: A Case Study of Bone-Cracking Hypercarnivores

    PubMed Central

    Tseng, Zhijie Jack

    2013-01-01

    Morphological convergence is a well documented phenomenon in mammals, and adaptive explanations are commonly employed to infer similar functions for convergent characteristics. I present a study that adopts aspects of theoretical morphology and engineering optimization to test hypotheses about adaptive convergent evolution. Bone-cracking ecomorphologies in Carnivora were used as a case study. Previous research has shown that skull deepening and widening are major evolutionary patterns in convergent bone-cracking canids and hyaenids. A simple two-dimensional design space, with skull width-to-length and depth-to-length ratios as variables, was used to examine optimized shapes for two functional properties: mechanical advantage (MA) and strain energy (SE). Functionality of theoretical skull shapes was studied using finite element analysis (FEA) and visualized as functional landscapes. The distribution of actual skull shapes in the landscape showed a convergent trend of plesiomorphically low-MA and moderate-SE skulls evolving towards higher-MA and moderate-SE skulls; this is corroborated by FEA of 13 actual specimens. Nevertheless, regions exist in the landscape where high-MA and lower-SE shapes are not represented by existing species; their vacancy is observed even at higher taxonomic levels. Results highlight the interaction of biomechanical and non-biomechanical factors in constraining general skull dimensions to localized functional optima through evolution. PMID:23734244

  11. EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

    EPA Science Inventory

    Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

  12. Review of Medical Image Classification using the Adaptive Neuro-Fuzzy Inference System

    PubMed Central

    Hosseini, Monireh Sheikh; Zekri, Maryam

    2012-01-01

    Image classification is an issue that utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification, and it is expected to be more developed in the future. Because of this fact, automatic diagnosis can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier in medical image classification during the past 16 years. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of an FIS with the learning power of artificial neural networks. The objective of ANFIS is to integrate the best features of fuzzy systems and neural networks. A brief comparison with other classifiers, main advantages and drawbacks of this classifier are investigated. PMID:23493054

  13. Review of Medical Image Classification using the Adaptive Neuro-Fuzzy Inference System.

    PubMed

    Hosseini, Monireh Sheikh; Zekri, Maryam

    2012-01-01

    Image classification is an issue that utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification, and it is expected to be more developed in the future. Because of this fact, automatic diagnosis can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier in medical image classification during the past 16 years. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of an FIS with the learning power of artificial neural networks. The objective of ANFIS is to integrate the best features of fuzzy systems and neural networks. A brief comparison with other classifiers, main advantages and drawbacks of this classifier are investigated.

  14. Synthetic shuffling and in vitro selection reveal the rugged adaptive fitness landscape of a kinase ribozyme

    PubMed Central

    Curtis, Edward A.; Bartel, David P.

    2013-01-01

    The relationship between genotype and phenotype is often described as an adaptive fitness landscape. In this study, we used a combination of recombination, in vitro selection, and comparative sequence analysis to characterize the fitness landscape of a previously isolated kinase ribozyme. Point mutations present in improved variants of this ribozyme were recombined in vitro in more than 1014 different arrangements using synthetic shuffling, and active variants were isolated by in vitro selection. Mutual information analysis of 65 recombinant ribozymes isolated in the selection revealed a rugged fitness landscape in which approximately one-third of the 91 pairs of positions analyzed showed evidence of correlation. Pairs of correlated positions overlapped to form densely connected networks, and groups of maximally connected nucleotides occurred significantly more often in these networks than they did in randomized control networks with the same number of links. The activity of the most efficient recombinant ribozyme isolated from the synthetically shuffled pool was 30-fold greater than that of any of the ribozymes used to build it, which indicates that synthetic shuffling can be a rich source of ribozyme variants with improved properties. PMID:23798664

  15. Acoustic model adaptation for ortolan bunting (Emberiza hortulana L.) song-type classification.

    PubMed

    Tao, Jidong; Johnson, Michael T; Osiejuk, Tomasz S

    2008-03-01

    Automatic systems for vocalization classification often require fairly large amounts of data on which to train models. However, animal vocalization data collection and transcription is a difficult and time-consuming task, so that it is expensive to create large data sets. One natural solution to this problem is the use of acoustic adaptation methods. Such methods, common in human speech recognition systems, create initial models trained on speaker independent data, then use small amounts of adaptation data to build individual-specific models. Since, as in human speech, individual vocal variability is a significant source of variation in bioacoustic data, acoustic model adaptation is naturally suited to classification in this domain as well. To demonstrate and evaluate the effectiveness of this approach, this paper presents the application of maximum likelihood linear regression adaptation to ortolan bunting (Emberiza hortulana L.) song-type classification. Classification accuracies for the adapted system are computed as a function of the amount of adaptation data and compared to caller-independent and caller-dependent systems. The experimental results indicate that given the same amount of data, supervised adaptation significantly outperforms both caller-independent and caller-dependent systems.

  16. Classification of local- and landscape-scale ecological types in the Southern Appalachian mountains

    SciTech Connect

    McNab, W.H.

    1996-12-31

    Five local ecological types based on vegetative communities and two landscape types based on groups of communities, were identified by integrating landform, soil, and vegetation components using multivariate techniques. Evaluation and several topographic and soil variables were highly correlated with types of both scales. Landscape ecological types based only on landform and soil variables without vegetation did not correspond with types developed using vegetation.

  17. Partitioning adaptive differentiation across a patchy landscape: shade avoidance traits in impatiens capensis.

    PubMed

    von Wettberg, Eric J; Remington, David L; Schmitt, Johanna

    2008-03-01

    Adaptation to different habitat types across a patchy landscape may either arise independently in each patch or occur due to repeated colonization of each patch by the same specialized genotype. We tested whether open- and closed-canopy forms of Impatiens capensis, an herbaceous annual plant of eastern North America, have evolved repeatedly by comparing hierarchical measures of F(ST) estimated from AFLPs to morphological differentiation measured by Q(ST) for five pairs of populations found in open and closed habitats in five New England regions. Morphological differentiation between habitats (Q(HT)) in elongation traits was greater than marker divergence (F(HT)), suggesting adaptive differentiation. Genotypes from open- and closed-canopy habitats differed in shade avoidance traits in several population pairs, whereas patterns of AFLP differentiation suggest this differentiation does not have a single origin. These results suggest that open- and closed-canopy habitats present different selective pressures, but that the outcome of diversifying selection may differ depending on specific closed- and open-canopy habitats and on starting genetic variation. Hierarchical partitioning of F(ST) and Q(ST) makes it possible to distinguish global stabilizing selection on traits across a landscape from diversifying selection between habitat types within regions.

  18. Noise-Tolerant Hyperspectral Signature Classification in Unresolved Object Detection with Adaptive Tabular Nearest Neighbor Encoding

    NASA Astrophysics Data System (ADS)

    Schmalz, M.; Key, G.

    Accurate spectral signature classification is a crucial step in the nonimaging detection and recognition of spaceborne objects. In classical hyperspectral recognition applications, especially where linear mixing models are employed, signature classification accuracy depends on accurate spectral endmember discrimination. In selected target recognition (ATR) applications, previous non-adaptive techniques for signature classification have yielded class separation and classifier refinement results that tend to be suboptimal. In practice, the number of signatures accurately classified often depends linearly on the number of inputs. This can lead to potentially severe classification errors in the presence of noise or densely interleaved signatures. In this paper, we present an enhancement of an emerging technology for nonimaging spectral signature classification based on a highly accurate, efficient search engine called Tabular Nearest Neighbor Encoding (TNE). Adaptive TNE can optimize its classifier performance to track input nonergodicities and yield measures of confidence or caution for evaluation of classification results. Unlike neural networks, TNE does not have a hidden intermediate data structure (e.g., a neural net weight matrix). Instead, TNE generates and exploits a user-accessible data structure called the agreement map (AM), which can be manipulated by Boolean logic operations to effect accurate classifier refinement through programmable algorithms. The open architecture and programmability of TNE's pattern-space (AM) processing allows a TNE developer to determine the qualitative and quantitative reasons for classification accuracy, as well as characterize in detail the signatures for which TNE does not obtain classification matches, and why such mis-matches occur. In this study AM-based classification has been modified to partially compensate for input statistical changes, in response to performance metrics such as probability of correct classification (Pd

  19. Regularized logistic regression with adjusted adaptive elastic net for gene selection in high dimensional cancer classification.

    PubMed

    Algamal, Zakariya Yahya; Lee, Muhammad Hisyam

    2015-12-01

    Cancer classification and gene selection in high-dimensional data have been popular research topics in genetics and molecular biology. Recently, adaptive regularized logistic regression using the elastic net regularization, which is called the adaptive elastic net, has been successfully applied in high-dimensional cancer classification to tackle both estimating the gene coefficients and performing gene selection simultaneously. The adaptive elastic net originally used elastic net estimates as the initial weight, however, using this weight may not be preferable for certain reasons: First, the elastic net estimator is biased in selecting genes. Second, it does not perform well when the pairwise correlations between variables are not high. Adjusted adaptive regularized logistic regression (AAElastic) is proposed to address these issues and encourage grouping effects simultaneously. The real data results indicate that AAElastic is significantly consistent in selecting genes compared to the other three competitor regularization methods. Additionally, the classification performance of AAElastic is comparable to the adaptive elastic net and better than other regularization methods. Thus, we can conclude that AAElastic is a reliable adaptive regularized logistic regression method in the field of high-dimensional cancer classification.

  20. Bayesian classification of polarimetric SAR images using adaptive a priori probabilities

    NASA Technical Reports Server (NTRS)

    Van Zyl, J. J.; Burnette, C. F.

    1992-01-01

    The problem of classifying earth terrain by observed polarimetric scattering properties is tackled with an iterative Bayesian scheme using a priori probabilities adaptively. The first classification is based on the use of fixed and not necessarily equal a priori probabilities, and successive iterations change the a priori probabilities adaptively. The approach is applied to an SAR image in which a single water body covers 10 percent of the image area. The classification accuracy for ocean, urban, vegetated, and total area increase, and the percentage of reclassified pixels decreases greatly as the iteration number increases. The iterative scheme is found to improve the a posteriori classification accuracy of maximum likelihood classifiers by iteratively using the local homogeneity in polarimetric SAR images. A few iterations can improve the classification accuracy significantly without sacrificing key high-frequency detail or edges in the image.

  1. Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

    PubMed

    Arbour, J H; López-Fernández, H

    2014-11-01

    Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade.

  2. Energy Landscape Reveals That the Budding Yeast Cell Cycle Is a Robust and Adaptive Multi-stage Process

    PubMed Central

    Lv, Cheng; Li, Xiaoguang; Li, Fangting; Li, Tiejun

    2015-01-01

    Quantitatively understanding the robustness, adaptivity and efficiency of cell cycle dynamics under the influence of noise is a fundamental but difficult question to answer for most eukaryotic organisms. Using a simplified budding yeast cell cycle model perturbed by intrinsic noise, we systematically explore these issues from an energy landscape point of view by constructing an energy landscape for the considered system based on large deviation theory. Analysis shows that the cell cycle trajectory is sharply confined by the ambient energy barrier, and the landscape along this trajectory exhibits a generally flat shape. We explain the evolution of the system on this flat path by incorporating its non-gradient nature. Furthermore, we illustrate how this global landscape changes in response to external signals, observing a nice transformation of the landscapes as the excitable system approaches a limit cycle system when nutrients are sufficient, as well as the formation of additional energy wells when the DNA replication checkpoint is activated. By taking into account the finite volume effect, we find additional pits along the flat cycle path in the landscape associated with the checkpoint mechanism of the cell cycle. The difference between the landscapes induced by intrinsic and extrinsic noise is also discussed. In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems. PMID:25794282

  3. Real-time dual-microphone noise classification for environment-adaptive pipelines of cochlear implants.

    PubMed

    Mirzahasanloo, Taher; Kehtarnavaz, Nasser

    2013-01-01

    This paper presents an improved noise classification in environment-adaptive speech processing pipelines of cochlear implants. This improvement is achieved by using a dual-microphone and by using a computationally efficient feature-level combination approach to achieve real-time operation. A new measure named Suppression Advantage is also defined in order to quantify the noise suppression improvement of an entire pipeline due to noise classification. The noise classification and suppression improvement results are presented for four commonly encountered noise environments.

  4. Verification of Hydrologic Landscape Derived Basin-Scale Classifications in the Pacific Northwest

    EPA Science Inventory

    The interaction between the physical properties of a catchment (form) and climatic forcing of precipitation and energy control how water is partitioned, stored, and conveyed through a catchment (function). Hydrologic Landscapes (HLs) were previously developed across Oregon and de...

  5. Non-parametric transient classification using adaptive wavelets

    NASA Astrophysics Data System (ADS)

    Varughese, Melvin M.; von Sachs, Rainer; Stephanou, Michael; Bassett, Bruce A.

    2015-11-01

    Classifying transients based on multiband light curves is a challenging but crucial problem in the era of GAIA and Large Synoptic Sky Telescope since the sheer volume of transients will make spectroscopic classification unfeasible. We present a non-parametric classifier that predicts the transient's class given training data. It implements two novel components: the use of the BAGIDIS wavelet methodology - a characterization of functional data using hierarchical wavelet coefficients - as well as the introduction of a ranked probability classifier on the wavelet coefficients that handles both the heteroscedasticity of the data in addition to the potential non-representativity of the training set. The classifier is simple to implement while a major advantage of the BAGIDIS wavelets is that they are translation invariant. Hence, BAGIDIS does not need the light curves to be aligned to extract features. Further, BAGIDIS is non-parametric so it can be used effectively in blind searches for new objects. We demonstrate the effectiveness of our classifier against the Supernova Photometric Classification Challenge to correctly classify supernova light curves as Type Ia or non-Ia. We train our classifier on the spectroscopically confirmed subsample (which is not representative) and show that it works well for supernova with observed light-curve time spans greater than 100 d (roughly 55 per cent of the data set). For such data, we obtain a Ia efficiency of 80.5 per cent and a purity of 82.4 per cent, yielding a highly competitive challenge score of 0.49. This indicates that our `model-blind' approach may be particularly suitable for the general classification of astronomical transients in the era of large synoptic sky surveys.

  6. Space Object Classification and Characterization Via Multiple Model Adaptive Estimation

    DTIC Science & Technology

    2014-07-14

    mathematical models of the same physical process or of the same model but dependent upon different constants or model parameters . The classification approach...Rodrigues Parameters (GRPs) resulting in a minimum parameter representation for the attitude state error.8 To within first order, the state error...i)|| 2 f2 + ||χδpk (i)|| 2 (10b) δq−k (i) = [ δ̺−k (i) δq−4k(i) ] (10c) where a is a parameter from 0 to 1 and f is a scale factor, which is often

  7. A just-in-time adaptive classification system based on the intersection of confidence intervals rule.

    PubMed

    Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel

    2011-10-01

    Classification systems meant to operate in nonstationary environments are requested to adapt when the process generating the observed data changes. A straightforward form of adaptation implementing the instance selection approach suggests releasing the obsolete data onto which the classifier is configured by replacing it with novel samples before retraining. In this direction, we propose an adaptive classifier based on the intersection of confidence intervals rule for detecting a possible change in the process generating the data as well as identifying the new data to be used to configure the classifier. A key point of the research is that no assumptions are made about the distribution of the process generating the data. Experimental results show that the proposed adaptive classification system is particularly effective in situations where the process is subject to abrupt changes.

  8. Targeting the adaptive molecular landscape of castration-resistant prostate cancer

    PubMed Central

    Wyatt, Alexander W; Gleave, Martin E

    2015-01-01

    Castration and androgen receptor (AR) pathway inhibitors induce profound and sustained responses in advanced prostate cancer. However, the inevitable recurrence is associated with reactivation of the AR and progression to a more aggressive phenotype termed castration-resistant prostate cancer (CRPC). AR reactivation can occur directly through genomic modification of the AR gene, or indirectly via co-factor and co-chaperone deregulation. This mechanistic heterogeneity is further complicated by the stress-driven induction of a myriad of overlapping cellular survival pathways. In this review, we describe the heterogeneous and evolvable molecular landscape of CRPC and explore recent successes and failures of therapeutic strategies designed to target AR reactivation and adaptive survival pathways. We also discuss exciting areas of burgeoning anti-tumour research, and their potential to improve the survival and management of patients with CRPC. PMID:25896606

  9. Developmental Structuralist Approach to the Classification of Adaptive and Pathologic Personality Organizations: Infancy and Early Childhood.

    ERIC Educational Resources Information Center

    Greenspan, Stanley I.; Lourie, Reginald S.

    This paper applies a developmental structuralist approach to the classification of adaptive and pathologic personality organizations and behavior in infancy and early childhood, and it discusses implications of this approach for preventive intervention. In general, as development proceeds, the structural capacity of the developing infant and child…

  10. An Analysis of Historic and Projected Climate Scenarios in the Western United States Using Hydrologic Landscape Classification

    NASA Astrophysics Data System (ADS)

    Jones, C., Jr.; Leibowitz, S. G.; Comeleo, R. L.; Stratton, L. E.; Sawicz, K. A.; Wigington, P. J., Jr.

    2015-12-01

    Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the Pacific Northwest. HLs are currently being applied across the Western U.S. to assess historic and projected climatic impacts. During the HL classification process, we analyze climate, seasonality, aquifer permeability, terrain, and soil permeability as the primary hydrologic drivers (and precipitation intensity as a secondary driver) associated with large scale hydrologic processes (storage, conveyance, and flow of water into or out of the watershed) in the West. Hypotheses regarding the dominant hydrologic pathways derived from the HL classification system are tested to corroborate or falsify these assumptions. Changes in climate are more likely to affect certain hydrogeologic parameters than others. For instance, changes in climate may result in changes in the magnitude, timing, or type of precipitation (snow vs. rain). Air temperature and the seasonality of dominant hydrologic processes may also be impacted. However, the effect of these changes on streamflow will depend on soil and aquifer permeability. In this analysis, we summarize (1) the HL classification methodology and (2) the use of historic (1900-present) PRISM climate data and climate projections to assess how changes in climate affect hydrologic processes and their associated impacts (e.g. water resource availability, ecological impacts, etc.) in the Western U.S.

  11. Using Hydrologic Landscape Classification to Evaluate the Hydrologic Effects of Climate in the Southwestern United States

    EPA Science Inventory

    Hydrologic landscapes (HLs) have been an active area of research at regional and national scales in the United States. The concept has been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the Pacific Northwe...

  12. Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate

    EPA Science Inventory

    Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

  13. An assessment of streamflow vulnerability to climate using Hydrologic Landscape classification

    EPA Science Inventory

    Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

  14. EVALUATION OF THE USE OF LANDSCAPE CLASSIFICATIONS FOR THE PREDICTION OF FRESHWATER BIOTA: SYNTHESIS AND RECOMMENDATIONS

    EPA Science Inventory

    This paper summarizes and synthesizes the collective results that emerged from the series of papers published in this issue of J-NABS, and places these results in the context of previously published literature describing variation in aquatic biota at landscape spatial scales. Cla...

  15. Classification of crops across heterogeneous agricultural landscape in Kenya using AisaEAGLE imaging spectroscopy data

    NASA Astrophysics Data System (ADS)

    Piiroinen, Rami; Heiskanen, Janne; Mõttus, Matti; Pellikka, Petri

    2015-07-01

    Land use practices are changing at a fast pace in the tropics. In sub-Saharan Africa forests, woodlands and bushlands are being transformed for agricultural use to produce food for the rapidly growing population. The objective of this study was to assess the prospects of mapping the common agricultural crops in highly heterogeneous study area in south-eastern Kenya using high spatial and spectral resolution AisaEAGLE imaging spectroscopy data. Minimum noise fraction transformation was used to pack the coherent information in smaller set of bands and the data was classified with support vector machine (SVM) algorithm. A total of 35 plant species were mapped in the field and seven most dominant ones were used as classification targets. Five of the targets were agricultural crops. The overall accuracy (OA) for the classification was 90.8%. To assess the possibility of excluding the remaining 28 plant species from the classification results, 10 different probability thresholds (PT) were tried with SVM. The impact of PT was assessed with validation polygons of all 35 mapped plant species. The results showed that while PT was increased more pixels were excluded from non-target polygons than from the polygons of the seven classification targets. This increased the OA and reduced salt-and-pepper effects in the classification results. Very high spatial resolution imagery and pixel-based classification approach worked well with small targets such as maize while there was mixing of classes on the sides of the tree crowns.

  16. Adaptive Road Crack Detection System by Pavement Classification

    PubMed Central

    Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

    2011-01-01

    This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement. PMID:22163717

  17. Adaptive road crack detection system by pavement classification.

    PubMed

    Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

    2011-01-01

    This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

  18. Diagnosis of streamflow prediction skills in Oregon using Hydrologic Landscape Classification

    EPA Science Inventory

    A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

  19. Where and why do models fail? Perspectives from Oregon Hydrologic Landscape classification

    EPA Science Inventory

    A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

  20. Object-based forest classification to facilitate landscape-scale conservation in the Mississippi Alluvial Valley

    USGS Publications Warehouse

    Mitchell, Michael; Wilson, R. Randy; Twedt, Daniel J.; Mini, Anne E.; James, J. Dale

    2016-01-01

    The Mississippi Alluvial Valley is a floodplain along the southern extent of the Mississippi River extending from southern Missouri to the Gulf of Mexico. This area once encompassed nearly 10 million ha of floodplain forests, most of which has been converted to agriculture over the past two centuries. Conservation programs in this region revolve around protection of existing forest and reforestation of converted lands. Therefore, an accurate and up to date classification of forest cover is essential for conservation planning, including efforts that prioritize areas for conservation activities. We used object-based image analysis with Random Forest classification to quickly and accurately classify forest cover. We used Landsat band, band ratio, and band index statistics to identify and define similar objects as our training sets instead of selecting individual training points. This provided a single rule-set that was used to classify each of the 11 Landsat 5 Thematic Mapper scenes that encompassed the Mississippi Alluvial Valley. We classified 3,307,910±85,344 ha (32% of this region) as forest. Our overall classification accuracy was 96.9% with Kappa statistic of 0.96. Because this method of forest classification is rapid and accurate, assessment of forest cover can be regularly updated and progress toward forest habitat goals identified in conservation plans can be periodically evaluated.

  1. Domain adaptation problems: a DASVM classification technique and a circular validation strategy.

    PubMed

    Bruzzone, Lorenzo; Marconcini, Mattia

    2010-05-01

    This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available only for a source domain different (even if related) from the target domain of (unlabeled) test data. Two main novel contributions are proposed: 1) a domain adaptation support vector machine (DASVM) technique which extends the formulation of support vector machines (SVMs) to the domain adaptation framework and 2) a circular indirect accuracy assessment strategy for validating the learning of domain adaptation classifiers when no true labels for the target--domain instances are available. Experimental results, obtained on a series of two-dimensional toy problems and on two real data sets related to brain computer interface and remote sensing applications, confirmed the effectiveness and the reliability of both the DASVM technique and the proposed circular validation strategy.

  2. Automatic and adaptive classification of electroencephalographic signals for brain computer interfaces.

    PubMed

    Rodríguez-Bermúdez, Germán; García-Laencina, Pedro J

    2012-11-01

    Extracting knowledge from electroencephalographic (EEG) signals has become an increasingly important research area in biomedical engineering. In addition to its clinical diagnostic purposes, in recent years there have been many efforts to develop brain computer interface (BCI) systems, which allow users to control external devices only by using their brain activity. Once the EEG signals have been acquired, it is necessary to use appropriate feature extraction and classification methods adapted to the user in order to improve the performance of the BCI system and, also, to make its design stage easier. This work introduces a novel fast adaptive BCI system for automatic feature extraction and classification of EEG signals. The proposed system efficiently combines several well-known feature extraction procedures and automatically chooses the most useful features for performing the classification task. Three different feature extraction techniques are applied: power spectral density, Hjorth parameters and autoregressive modelling. The most relevant features for linear discrimination are selected using a fast and robust wrapper methodology. The proposed method is evaluated using EEG signals from nine subjects during motor imagery tasks. Obtained experimental results show its advantages over the state-of-the-art methods, especially in terms of classification accuracy and computational cost.

  3. Landscape genomics and a common garden trial reveal adaptive differentiation to temperature across Europe in the tree species Alnus glutinosa.

    PubMed

    De Kort, Hanne; Vandepitte, Katrien; Bruun, Hans Henrik; Closset-Kopp, Déborah; Honnay, Olivier; Mergeay, Joachim

    2014-10-01

    The adaptive potential of tree species to cope with climate change has important ecological and economic implications. Many temperate tree species experience a wide range of environmental conditions, suggesting high adaptability to new environmental conditions. We investigated adaptation to regional climate in the drought-sensitive tree species Alnus glutinosa (Black alder), using a complementary approach that integrates genomic, phenotypic and landscape data. A total of 24 European populations were studied in a common garden and through landscape genomic approaches. Genotyping-by-sequencing was used to identify SNPs across the genome, resulting in 1990 SNPs. Although a relatively low percentage of putative adaptive SNPs was detected (2.86% outlier SNPs), we observed clear associations among outlier allele frequencies, temperature and plant traits. In line with the typical drought avoiding nature of A. glutinosa, leaf size varied according to a temperature gradient and significant associations with multiple outlier loci were observed, corroborating the ecological relevance of the observed outlier SNPs. Moreover, the lack of isolation by distance, the very low genetic differentiation among populations and the high intrapopulation genetic variation all support the notion that high gene exchange combined with strong environmental selection promotes adaptation to environmental cues.

  4. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-03-19

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  5. CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

    PubMed

    Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

    2016-12-07

    In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

  6. Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

    NASA Astrophysics Data System (ADS)

    Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

    2014-03-01

    A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

  7. Meeting review. Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics.

    PubMed

    Joost, Stéphane; Vuilleumier, Séverine; Jensen, Jeffrey D; Schoville, Sean; Leempoel, Kevin; Stucki, Sylvie; Widmer, Ivo; Melodelima, Christelle; Rolland, Jonathan; Manel, Stéphanie

    2013-07-01

    A workshop recently held at the École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

  8. Adaptation of motor imagery EEG classification model based on tensor decomposition

    NASA Astrophysics Data System (ADS)

    Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Keng Ang, Kai; Ong, Sim Heng

    2014-10-01

    Objective. Session-to-session nonstationarity is inherent in brain-computer interfaces based on electroencephalography. The objective of this paper is to quantify the mismatch between the training model and test data caused by nonstationarity and to adapt the model towards minimizing the mismatch. Approach. We employ a tensor model to estimate the mismatch in a semi-supervised manner, and the estimate is regularized in the discriminative objective function. Main results. The performance of the proposed adaptation method was evaluated on a dataset recorded from 16 subjects performing motor imagery tasks on different days. The classification results validated the advantage of the proposed method in comparison with other regularization-based or spatial filter adaptation approaches. Experimental results also showed that there is a significant correlation between the quantified mismatch and the classification accuracy. Significance. The proposed method approached the nonstationarity issue from the perspective of data-model mismatch, which is more direct than data variation measurement. The results also demonstrated that the proposed method is effective in enhancing the performance of the feature extraction model.

  9. Epithelium-stroma classification via convolutional neural networks and unsupervised domain adaptation in histopathological images.

    PubMed

    Huang, Yue; Zheng, Han; Liu, Chi; Ding, Xinghao; Rohde, Gustavo

    2017-04-06

    Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications. A very simple but effective deep learning method, that introduces the concept of unsupervised domain adaptation to a simple convolutional neural network (CNN), has been proposed in this paper. Inspired by transfer learning, our work assumes that the training data and testing data follow different distributions, and there is an adaptation operation to more accurately estimate the kernels in CNN in feature extraction, in order to enhance performance by transferring knowledge from labeled data in source domain to unlabeled data in target domain. The model has been evaluated using three independent public epithelium-stroma datasets by cross-dataset validations. The experimental results demonstrate that for epithelium-stroma classification, the proposed framework outperforms the state-of-the-art deep neural network model, and it also achieves better performance than other existing deep domain adaptation methods. The proposed model can be considered to be a better option for real-world applications in histopathological image analysis, since there is no longer a requirement for large-scale labeled data in each specified domain.

  10. Adaptive polarimetric sensing for optimum radar signature classification using a genetic search algorithm.

    PubMed

    Sadjadi, Firooz A

    2006-08-01

    An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.

  11. Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

    NASA Astrophysics Data System (ADS)

    Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

    2014-02-01

    This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

  12. Collaborative adaptive landscape management (CALM) in rangelands: Discussion of general principles

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The management of rangeland landscapes involves broad spatial extents, mixed land ownership, and multiple resource objectives. Management outcomes depend on biophysical heterogeneity, highly variable weather conditions, land use legacies, and spatial processes such as wildlife movement, hydrological...

  13. Domain adaptation based on deep denoising auto-encoders for classification of remote sensing images

    NASA Astrophysics Data System (ADS)

    Riz, Emanuele; Demir, Begüm; Bruzzone, Lorenzo

    2016-10-01

    This paper investigates the effectiveness of deep learning (DL) for domain adaptation (DA) problems in the classification of remote sensing images to generate land-cover maps. To this end, we introduce two different DL architectures: 1) single-stage domain adaptation (SS-DA) architecture; and 2) hierarchal domain adaptation (H-DA) architecture. Both architectures require that a reliable training set is available only for one of the images (i.e., the source domain) from a previous analysis, whereas it is not for another image to be classified (i.e., the target domain). To classify the target domain image, the proposed architectures aim to learn a shared feature representation that is invariant across the source and target domains in a completely unsupervised fashion. To this end, both architectures are defined based on the stacked denoising auto-encoders (SDAEs) due to their high capability to define high-level feature representations. The SS-DA architecture leads to a common feature space by: 1) initially unifying the samples in source and target domains; and 2) then feeding them simultaneously into the SDAE. To further increase the robustness of the shared representations, the H-DA employs: 1) two SDAEs for learning independently the high level representations of source and target domains; and 2) a consensus SDAE to learn the domain invariant high-level features. After obtaining the domain invariant features through proposed architectures, the classifier is trained by the domain invariant labeled samples of the source domain, and then the domain invariant samples of the target domain are classified to generate the related classification map. Experimental results obtained for the classification of very high resolution images confirm the effectiveness of the proposed DL architectures.

  14. Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification

    PubMed Central

    Ayanu, Yohannes; Conrad, Christopher; Jentsch, Anke; Koellner, Thomas

    2015-01-01

    The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential. PMID:26098107

  15. Detection and Classification of Motor Vehicle Noise in a Forested Landscape

    NASA Astrophysics Data System (ADS)

    Brown, Casey L.; Reed, Sarah E.; Dietz, Matthew S.; Fristrup, Kurt M.

    2013-11-01

    Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.

  16. Sampling network stratification by terrain classification in eroded agricultural landscapes at plot scale

    NASA Astrophysics Data System (ADS)

    Penížek, Vít; Zádorová, Tereza; Kodešová, Radka

    2015-04-01

    The description of soil properties variability is important aspect in land management and food production at plot scale. We describe novelty approach for design of sampling network on agricultural plots with high relief variability. The terrain properties were used for improved spatial prediction of soil properties including design of the sampling network. Regular sampling network, random sampling network, systematic unaligned sampling network and stratified sampling network schemes were compared to prove the advantages of relief based stratified sampling networks. The study was performed for humus horizon depth prediction on agriculture plot of 6.5 ha with dissected relief where originally homogenous soil cover was differentiated by erosion and sedimentation into mosaic of Chernozem, Regosol and colluvial soils. Moreover the comparison was done on three levels of sampling density (65, 40 and 24 sampling points). The stratification of sampling network was based on unsupervised relief classification. The performance of the soil properties prediction based on different sampling network was assesed by RMSE calculation based on predicted values versus validation dataset. According the RMSE, the stratified sampling network performed the best (7.4 cm) comparing the regular sampling network (10.8 cm), random sampling network (17.7 cm) and systematic unaligned sampling network (11.2 cm). The accuracy of the soil properties spatial prediction decreased with the decreasing number of sampling points, but the stratified network performed significantly better that other used methods. The study showed that, for soil properties spatial variability description at certain accuracy level, relief-based stratified network can contain 25 % less sampling points comparing to regular network. This leads to potential financial and person cost reduction for the soil survey. The study was supported by grant nr. 13-07516P of the Czech science foundation and by grant nr. QJ1230319 of the

  17. Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

    PubMed Central

    Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

    2015-01-01

    The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120

  18. Classification

    ERIC Educational Resources Information Center

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  19. Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maximum Likelihood

    NASA Astrophysics Data System (ADS)

    Gupta, Kinjal Dhar; Vilalta, Ricardo; Asadourian, Vicken; Macri, Lucas

    2014-05-01

    We describe an approach to automate the classification of Cepheid variable stars into two subtypes according to their pulsation mode. Automating such classification is relevant to obtain a precise determination of distances to nearby galaxies, which in addition helps reduce the uncertainty in the current expansion of the universe. One main difficulty lies in the compatibility of models trained using different galaxy datasets; a model trained using a training dataset may be ineffectual on a testing set. A solution to such difficulty is to adapt predictive models across domains; this is necessary when the training and testing sets do not follow the same distribution. The gist of our methodology is to train a predictive model on a nearby galaxy (e.g., Large Magellanic Cloud), followed by a model-adaptation step to make the model operable on other nearby galaxies. We follow a parametric approach to density estimation by modeling the training data (anchor galaxy) using a mixture of linear models. We then use maximum likelihood to compute the right amount of variable displacement, until the testing data closely overlaps the training data. At that point, the model can be directly used in the testing data (target galaxy).

  20. Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier.

    PubMed

    Ibrahim, Sulaimon; Chowriappa, Pradeep; Dua, Sumeet; Acharya, U Rajendra; Noronha, Kevin; Bhandary, Sulatha; Mugasa, Hatwib

    2015-12-01

    Prolonged diabetes retinopathy leads to diabetes maculopathy, which causes gradual and irreversible loss of vision. It is important for physicians to have a decision system that detects the early symptoms of the disease. This can be achieved by building a classification model using machine learning algorithms. Fuzzy logic classifiers group data elements with a degree of membership in multiple classes by defining membership functions for each attribute. Various methods have been proposed to determine the partitioning of membership functions in a fuzzy logic inference system. A clustering method partitions the membership functions by grouping data that have high similarity into clusters, while an equalized universe method partitions data into predefined equal clusters. The distribution of each attribute determines its partitioning as fine or coarse. A simple grid partitioning partitions each attribute equally and is therefore not effective in handling varying distribution amongst the attributes. A data-adaptive method uses a data frequency-driven approach to partition each attribute based on the distribution of data in that attribute. A data-adaptive neuro-fuzzy inference system creates corresponding rules for both finely distributed and coarsely distributed attributes. This method produced more useful rules and a more effective classification system. We obtained an overall accuracy of 98.55%.

  1. Effect of mutators on adaptability in time-varying fitness landscapes

    NASA Astrophysics Data System (ADS)

    Gorodetsky, Pavel; Tannenbaum, Emmanuel

    2008-04-01

    This Brief Report studies the quasispecies dynamics of a population capable of genetic repair evolving on a time-dependent fitness landscape. We develop a model that considers an asexual population of single-stranded, conservatively replicating genomes, whose only source of genetic variation is due to copying errors during replication. We consider a time-dependent, single-fitness-peak landscape where the master sequence changes by a single point mutation at every time τ . We are able to analytically solve for the evolutionary dynamics of the population in the point-mutation limit. In particular, our model provides an analytical expression for the fraction of mutators in the dynamic fitness landscape that agrees well with results from stochastic simulations.

  2. Using Pattern Classification to Measure Adaptation to the Orientation of High Order Aberrations

    PubMed Central

    Sawides, Lucie; Dorronsoro, Carlos; Haun, Andrew M.; Peli, Eli; Marcos, Susana

    2013-01-01

    Background The image formed by the eye's optics is blurred by the ocular aberrations, specific to each eye. Recent studies demonstrated that the eye is adapted to the level of blur produced by the high order aberrations (HOA). We examined whether visual coding is also adapted to the orientation of the natural HOA of the eye. Methods and Findings Judgments of perceived blur were measured in 5 subjects in a psychophysical procedure inspired by the “Classification Images” technique. Subjects were presented 500 pairs of images, artificially blurred with HOA from 100 real eyes (i.e. different orientations), with total blur level adjusted to match the subject's natural blur. Subjects selected the image that appeared best focused in each random pair, in a 6-choice ranked response. Images were presented through Adaptive Optics correction of the subject's aberrations. The images selected as best focused were identified as positive, the other as negative responses. The highest classified positive responses correlated more with the subject's Point Spread Function, PSF, (r = 0.47 on average) than the negative (r = 0.34) and the difference was significant for all subjects (p<0.02). Using the orientation of the best fitting ellipse of angularly averaged integrated PSF intensities (weighted by the subject's responses) we found that in 4 subjects the positive PSF response was close to the subject's natural PSF orientation (within 21 degrees on average) whereas the negative PSF response was almost perpendicularly oriented to the natural PSF (at 76 degrees on average). Conclusions The Classification-Images inspired method is very powerful in identifying the internally coded blur of subjects. The consistent bias of the Positive PSFs towards the natural PSF in most subjects indicates that the internal code of blur appears rather specific to each subject's high order aberrations and reveals that the calibration mechanisms for normalizing blur also operate using orientation

  3. Automatic target classification of slow moving ground targets using space-time adaptive processing

    NASA Astrophysics Data System (ADS)

    Malas, John Alexander

    2002-04-01

    Air-to-ground surveillance radar technologies are increasingly being used by theater commanders to detect, track, and identify ground moving targets. New radar automatic target recognition (ATR) technologies are being developed to aid the pilot in assessing the ground combat picture. Most air-to-ground surveillance radars use Doppler filtering techniques to separate target returns from ground clutter. Unfortunately, Doppler filter techniques fall short on performance when target geometry and ground vehicle speed result in low line of sight velocities. New clutter filter techniques compatible with emerging advancements in wideband radar operation are needed to support surveillance modes of radar operation when targets enter this low velocity regime. In this context, space-time adaptive processing (STAP) in conjunction with other algorithms offers a class of signal processing that provide improved target detection, tracking, and classification in the presence of interference through the adaptive nulling of both ground clutter and/or jamming. Of particular interest is the ability of the radar to filter and process the complex target signature data needed to generate high range resolution (HRR) signature profiles on ground targets. A new approach is proposed which will allow air-to-ground target classification of slow moving vehicles in clutter. A wideband STAP approach for clutter suppression is developed which preserves the amplitude integrity of returns from multiple range bins consistent with the HRR ATR approach. The wideband STAP processor utilizes narrowband STAP principles to generate a series of adaptive sub-band filters. Each sub-band filter output is used to construct the complete filtered response of the ground target. The performance of this new approach is demonstrated and quantified through the implementation of a one dimensional template-based minimum mean squared error classifier. Successful minimum velocity identification is defined in terms of

  4. Applying ecological site concepts to adaptive conservation management on an iconic Californian landscape

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Tejon Ranch is a spectacular landscape valued for its biological diversity, livestock production, and cultural heritage. Situated at the convergence of three of California’s major biogeographic zones, it is the largest, contiguous private property in the state. Since 2008, the ranch has operated und...

  5. Adapted Verbal Feedback, Instructor Interaction and Student Emotions in the Landscape Architecture Studio

    ERIC Educational Resources Information Center

    Smith, Carl A.; Boyer, Mark E.

    2015-01-01

    In light of concerns with architectural students' emotional jeopardy during traditional desk and final-jury critiques, the authors pursue alternative approaches intended to provide more supportive and mentoring verbal assessment in landscape architecture studios. In addition to traditional studio-based critiques throughout a semester, we provide…

  6. Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

    PubMed Central

    Hussain, Shaista; Basu, Arindam

    2016-01-01

    The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best “k” out of “d” inputs to make connections on every dendritic branch (k < < d). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other

  7. Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity.

    PubMed

    Hussain, Shaista; Basu, Arindam

    2016-01-01

    The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best "k" out of "d" inputs to make connections on every dendritic branch (k < < d). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other spike

  8. Expanding the prevention armamentarium portfolio: a framework for promoting HIV-Conversant Communities within a complex, adaptive epidemiological landscape.

    PubMed

    Burman, Christopher J; Aphane, Marota; Mtapuri, Oliver; Delobelle, Peter

    2015-01-01

    The article describes a design journey that culminated in an HIV-Conversant Community Framework that is now being piloted in the Limpopo Province of South Africa. The objective of the initiative is to reduce the aggregate community viral load by building capacity at multiple scales that strengthens peoples' HIV-related navigational skill sets-while simultaneously opening a 'chronic situation' schema. The framework design is based upon a transdisciplinary methodological combination that synthesises ideas and constructs from complexity science and the management sciences as a vehicle through which to re-conceptualise HIV prevention. This resulted in a prototype that included the following constructs: managing HIV-prevention in a complex, adaptive epidemiological landscape; problematising and increasing the scope of the HIV knowledge armamentarium through education that focuses on the viral load and Langerhans cells; disruptive innovation and safe-fail probes followed by the facilitation of path creations and pattern management implementation techniques. These constructs are underpinned by a 'middle-ground' prevention approach which is designed to bridge the prevention 'fault line', enabling a multi-ontology conceptualisation of the challenge to be developed. The article concludes that stepping outside of the 'ordered' epistemological parameters of the existing prevention 'messaging' mind-set towards a more systemic approach that emphasises agency, structure and social practices as a contribution to 'ending AIDS by 2030' is worthy of further attention if communities are to engage more adaptively with the dynamic HIV landscape in South Africa.

  9. Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions.

    PubMed

    Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

    2013-04-09

    The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy.

  10. EEG-Based BCI System Using Adaptive Features Extraction and Classification Procedures

    PubMed Central

    Mangia, Anna Lisa; Cappello, Angelo

    2016-01-01

    Motor imagery is a common control strategy in EEG-based brain-computer interfaces (BCIs). However, voluntary control of sensorimotor (SMR) rhythms by imagining a movement can be skilful and unintuitive and usually requires a varying amount of user training. To boost the training process, a whole class of BCI systems have been proposed, providing feedback as early as possible while continuously adapting the underlying classifier model. The present work describes a cue-paced, EEG-based BCI system using motor imagery that falls within the category of the previously mentioned ones. Specifically, our adaptive strategy includes a simple scheme based on a common spatial pattern (CSP) method and support vector machine (SVM) classification. The system's efficacy was proved by online testing on 10 healthy participants. In addition, we suggest some features we implemented to improve a system's “flexibility” and “customizability,” namely, (i) a flexible training session, (ii) an unbalancing in the training conditions, and (iii) the use of adaptive thresholds when giving feedback. PMID:27635129

  11. SSD-Optimized Workload Placement with Adaptive Learning and Classification in HPC Environments

    SciTech Connect

    Wan, Lipeng; Lu, Zheng; Cao, Qing; Wang, Feiyi; Oral, H Sarp; Settlemyer, Bradley W

    2014-01-01

    In recent years, non-volatile memory devices such as SSD drives have emerged as a viable storage solution due to their increasing capacity and decreasing cost. Due to the unique capability and capacity requirements in large scale HPC (High Performance Computing) storage environment, a hybrid config- uration (SSD and HDD) may represent one of the most available and balanced solutions considering the cost and performance. Under this setting, effective data placement as well as movement with controlled overhead become a pressing challenge. In this paper, we propose an integrated object placement and movement framework and adaptive learning algorithms to address these issues. Specifically, we present a method that shuffle data objects across storage tiers to optimize the data access performance. The method also integrates an adaptive learning algorithm where real- time classification is employed to predict the popularity of data object accesses, so that they can be placed on, or migrate between SSD or HDD drives in the most efficient manner. We discuss preliminary results based on this approach using a simulator we developed to show that the proposed methods can dynamically adapt storage placements and access pattern as workloads evolve to achieve the best system level performance such as throughput.

  12. Landscape risk factors for Lyme disease in the eastern broadleaf forest province of the Hudson River valley and the effect of explanatory data classification resolution.

    PubMed

    Messier, Kyle P; Jackson, Laura E; White, Jennifer L; Hilborn, Elizabeth D

    2015-01-01

    This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity) and aggregate classes (e.g., forest, developed). Percent of each landcover type, median income, and centroid coordinates were calculated by census tract. Regression results from individual and aggregate variable models were compared with the dispersion parameter-based R(2) (Rα(2)) and AIC. The maximum Rα(2) was 0.82 and 0.83 for the best aggregate and individual model, respectively. The AICs for the best models differed by less than 0.5%. The aggregate model variables included forest, developed, agriculture, agriculture-squared, y-coordinate, y-coordinate-squared, income and income-squared. The individual model variables included deciduous forest, deciduous forest-squared, developed low intensity, pasture, y-coordinate, y-coordinate-squared, income, and income-squared. Results indicate that regional landscape models for Lyme disease rate are robust to NLCD landcover classification resolution.

  13. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation.

    PubMed

    Fitzpatrick, Matthew C; Keller, Stephen R

    2015-01-01

    Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability.

  14. Social Networks and Adaptation to Environmental Change: The Case of Central Oregon's Fire-Prone Forest Landscape

    NASA Astrophysics Data System (ADS)

    Fischer, A.

    2012-12-01

    Social networks are the patterned interactions among individuals and organizations through which people refine their beliefs and values, negotiate meanings for things and develop behavioral intentions. The structure of social networks has bearing on how people communicate information, generate and retain knowledge, make decisions and act collectively. Thus, social network structure is important for how people perceive, shape and adapt to the environment. We investigated the relationship between social network structure and human adaptation to wildfire risk in the fire-prone forested landscape of Central Oregon. We conducted descriptive and non-parametric social network analysis on data gathered through interviews to 1) characterize the structure of the network of organizations involved in forest and wildfire issues and 2) determine whether network structure is associated with organizations' beliefs, values and behaviors regarding fire and forest management. Preliminary findings indicate that fire protection and forest-related organizations do not frequently communicate or cooperate, suggesting that opportunities for joint problem-solving, innovation and collective action are limited. Preliminary findings also suggest that organizations with diverse partners are more likely to hold adaptive beliefs about wildfire and work cooperatively. We discuss the implications of social network structure for adaptation to changing environmental conditions such as wildfire risk.

  15. Factors shaping the adaptive landscape for arboviruses: implications for the emergence of disease

    PubMed Central

    Coffey, Lark L; Forrester, Naomi; Tsetsarkin, Konstantin; Vasilakis, Nikos; Weaver, Scott C

    2013-01-01

    Many examples of the emergence or re-emergence of infectious diseases involve the adaptation of zoonotic viruses to new amplification hosts or to humans themselves. These include several instances of simple mutational adaptations, often to hosts closely related to the natural reservoirs. However, based on theoretical grounds, arthropod-borne viruses, or arboviruses, may face several challenges for adaptation to new hosts. Here, we review recent findings regarding adaptive evolution of arboviruses and its impact on disease emergence. We focus on the zoonotic alphaviruses Venezuelan equine encephalitis and chikungunya viruses, which have undergone adaptive evolution that mediated recent outbreaks of disease, as well as the flaviviruses dengue and West Nile viruses, which have emerged via less dramatic adaptive mechanisms. PMID:23374123

  16. Development of a Digital Aquifer Permeability Map for the Pacific Southwest in Support of Hydrologic Landscape Classification: Methods

    EPA Science Inventory

    Researchers at the U.S. Environmental Protection Agency’s Western Ecology Division have been developing hydrologic landscape maps for selected U.S. states in an effort to create a method to identify the intrinsic watershed attributes of landscapes in regions with little dat...

  17. Learning self-adaptive color harmony model for aesthetic quality classification

    NASA Astrophysics Data System (ADS)

    Kuang, Zhijie; Lu, Peng; Wang, Xiaojie; Lu, Xiaofeng

    2015-03-01

    Color harmony is one of the key aspects in aesthetic quality classification for photos. The existing color harmony models either are in lack of quantization schemes or can assess simple color patterns only. Therefore, these models cannot be applied to assess color harmony of photos directly. To address this problem, we proposed a simple data-based self-adaptive color harmony model. In this model, the hue distribution of a photo is fitted by mean shift based method, then features are extracted according to this distribution and finally the Gaussian mixture model is applied for learning features extracted from all the photos. The experimental results on eight categories datasets show that the proposed method outperforms the classic rule-based methods and the state-of-the-art data-based model.

  18. Adaptive descriptor based on the geometric consistency of local image features: application to flower image classification

    NASA Astrophysics Data System (ADS)

    Najjar, Asma; Zagrouba, Ezzeddine

    2016-09-01

    Geometric consistency is, usually, considered as a postprocessing step to filter matched sets of local features in order to discard outliers. In this work, it is used to propose an adaptive feature that describes the geometric dispersion of keypoints. It is based on a distribution computed by a nonparametric estimator so that no assumption is made about the data. We investigated and discussed the invariance properties of our descriptor under the most common two- and three-dimensional transformations. Then, we applied it to flower recognition. The classification is performed using the precomputed kernel of support vector machines classifier. Indeed, a similarity computing framework that uses the Kullback-Leibler divergence is presented. Furthermore, a customized layout for each flower image is designed to describe and compare separately the boundary and the central area of flowers. Experimentations made on the Oxford flower-17 dataset prove the efficiency of our method in terms of classification accuracy and computational complexity. The limits of our descriptor are also discussed on a 10-class subset of the Oxford flower-102 dataset.

  19. An adaptive method with integration of multi-wavelet based features for unsupervised classification of SAR images

    NASA Astrophysics Data System (ADS)

    Chamundeeswari, V. V.; Singh, D.; Singh, K.

    2007-12-01

    In single band and single polarized synthetic aperture radar (SAR) images, the information is limited to intensity and texture only and it is very difficult to interpret such SAR images without any a priori information. For unsupervised classification of SAR images, M-band wavelet decomposition is performed on the SAR image and sub-band selection on the basis of energy levels is applied to improve the classification results since sparse representation of sub-bands degrades the performance of classification. Then, textural features are obtained from selected sub-bands and integrated with intensity features. An adaptive neuro-fuzzy algorithm is used to improve computational efficiency by extracting significant features. K-means classification is performed on the extracted features and land features are labeled. This classification algorithm involves user defined parameters. To remove the user dependency and to obtain maximum achievable classification accuracy, an algorithm is developed in this paper for classification accuracy in terms of the parameters involved in the segmentation process. This is very helpful to develop the automated land-cover monitoring system with SAR, where optimized parameters are to be identified only once and these parameters can be applied to SAR imagery of the same scene obtained year after year. A single band, single polarized SAR image is classified into water, urban and vegetation areas using this method and overall classification accuracy is obtained in the range of 85.92%-93.70% by comparing with ground truth data.

  20. Cultural adaptation, content validity and inter-rater reliability of the "STAR Skin Tear Classification System"1

    PubMed Central

    Strazzieri-Pulido, Kelly Cristina; Santos, Vera Lúcia Conceição de Gouveia; Carville, Keryln

    2015-01-01

    AIMS: to perform the cultural adaptation of the STAR Skin Tear Classification System into the Portuguese language and to test the content validity and inter-rater reliability of the adapted version. METHODS: methodological study with a quantitative approach. The cultural adaptation was developed in three phases: translation, evaluation by a committee of judges and back-translation. The instrument was tested regarding content validity and inter-rater reliability. RESULTS: the adapted version obtained a regular level of concordance when it was applied by nurses using photographs of friction injuries. Regarding its application in clinical practice, the adapted version obtained a moderate and statistically significant level of concordance. CONCLUSION: the study tested the content validity and inter-rater reliability of the version adapted into the Portuguese language. Its inclusion in clinical practice will enable the correct identification of this type of injury, as well as the implementation of protocols for the prevention and treatment of friction injuries. PMID:25806644

  1. An adaptive threshold based image processing technique for improved glaucoma detection and classification.

    PubMed

    Issac, Ashish; Partha Sarathi, M; Dutta, Malay Kishore

    2015-11-01

    Glaucoma is an optic neuropathy which is one of the main causes of permanent blindness worldwide. This paper presents an automatic image processing based method for detection of glaucoma from the digital fundus images. In this proposed work, the discriminatory parameters of glaucoma infection, such as cup to disc ratio (CDR), neuro retinal rim (NRR) area and blood vessels in different regions of the optic disc has been used as features and fed as inputs to learning algorithms for glaucoma diagnosis. These features which have discriminatory changes with the occurrence of glaucoma are strategically used for training the classifiers to improve the accuracy of identification. The segmentation of optic disc and cup based on adaptive threshold of the pixel intensities lying in the optic nerve head region. Unlike existing methods the proposed algorithm is based on an adaptive threshold that uses local features from the fundus image for segmentation of optic cup and optic disc making it invariant to the quality of the image and noise content which may find wider acceptability. The experimental results indicate that such features are more significant in comparison to the statistical or textural features as considered in existing works. The proposed work achieves an accuracy of 94.11% with a sensitivity of 100%. A comparison of the proposed work with the existing methods indicates that the proposed approach has improved accuracy of classification glaucoma from a digital fundus which may be considered clinically significant.

  2. Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

    PubMed Central

    Gaspar-Cunha, A.; Recio, G.; Costa, L.; Estébanez, C.

    2014-01-01

    Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier. PMID:24707201

  3. Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

    PubMed

    Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

    2016-05-01

    Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches.

  4. Self-adaptive MOEA feature selection for classification of bankruptcy prediction data.

    PubMed

    Gaspar-Cunha, A; Recio, G; Costa, L; Estébanez, C

    2014-01-01

    Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier.

  5. Pathogen population bottlenecks and adaptive landscapes: overcoming the barriers to disease emergence.

    PubMed

    Geoghegan, Jemma L; Senior, Alistair M; Holmes, Edward C

    2016-08-31

    Emerging diseases are a major challenge to public health. Revealing the evolutionary processes that allow novel pathogens to adapt to new hosts, also the potential barriers to host adaptation, is central to understanding the drivers of disease emergence. In particular, it is unclear how the genetics and ecology of pathogens interact to shape the likelihood of successful cross-species transmission. To better understand the determinants of host adaptation and emergence, we modelled key aspects of pathogen evolutionary dynamics at both intra- and inter-host scales, using parameter values similar to those observed in influenza virus. We considered the possibility of acquiring the necessary host adaptive mutations both before ('off-the-shelf' emergence) and after ('tailor-made' emergence) a virus is transmitted from a donor to a new recipient species. Under both scenarios, population bottlenecks at inter-host transmission act as a major barrier to host adaptation, greatly limiting the number of adaptive mutations that are able to cross the species barrier. In addition, virus emergence is hindered if the fitness valley between the donor and recipient hosts is either too steep or too shallow. Overall, our results reveal where in evolutionary parameter space a virus could adapt to and become transmissible in a new species.

  6. Virtual-system-coupled adaptive umbrella sampling to compute free-energy landscape for flexible molecular docking.

    PubMed

    Higo, Junichi; Dasgupta, Bhaskar; Mashimo, Tadaaki; Kasahara, Kota; Fukunishi, Yoshifumi; Nakamura, Haruki

    2015-07-30

    A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did.

  7. The genomic landscape of rapid repeated evolutionary adaptation to toxic pollution in wild fish

    EPA Science Inventory

    Atlantic killifish populations have rapidly adapted to normally lethal levels of pollution in four urban estuaries. Through analysis of 384 whole killifish genome sequences and comparative transcriptomics in four pairs of sensitive and tolerant populations, we identify the aryl h...

  8. Gravitational self-organizing map-based seismic image classification with an adaptive spectral-textural descriptor

    NASA Astrophysics Data System (ADS)

    Hao, Yanling; Sun, Genyun

    2016-10-01

    Seismic image classification is of vital importance for extracting damage information and evaluating disaster losses. With the increasing availability of high resolution remote sensing images, automatic image classification offers a unique opportunity to accommodate the rapid damage mapping requirements. However, the diversity of disaster types and the lack of uniform statistical characteristics in seismic images increase the complexity of automated image classification. This paper presents a novel automatic seismic image classification approach by integrating an adaptive spectral-textural descriptor into gravitational self-organizing map (gSOM). In this approach, seismic image is first segmented into several objects based on mean shift (MS) method. These objects are then characterized explicitly by spectral and textural feature quantization histograms. To objectify the image object delineation adapt to various disaster types, an adaptive spectral-textural descriptor is developed by integrating the histograms automatically. Subsequently, these objects as classification units are represented by neurons in a self-organizing map and clustered by adjacency gravitation. By moving the neurons around the gravitational space and merging them according to the gravitation, the object-based gSOM is able to find arbitrary shape and determine the class number automatically. Taking advantage of the diversity of gSOM results, consensus function is then conducted to discover the most suitable classification result. To confirm the validity of the presented approach, three aerial seismic images in Wenchuan covering several disaster types are utilized. The obtained quantitative and qualitative experimental results demonstrated the feasibility and accuracy of the proposed seismic image classification method.

  9. Noise-Robust Spectral Signature Classification in Non-resolved Object Detection using Feedback Controlled Adaptive Learning

    NASA Astrophysics Data System (ADS)

    Schmalz, M.; Key, G.

    2012-09-01

    Accurate spectral signature classification is key to reliable nonresolved detection and recognition of spaceborne objects. In classical signature-based recognition applications, classification accuracy has been shown to depend on accurate spectral endmember discrimination. Unfortunately, signatures are corrupted by noise and clutter that can be nonergodic in astronomical imaging practice. In previous work, we have shown that object class separation and classifier refinement results can be severely corrupted by input noise, leading to suboptimal classification. We have also shown that computed pattern recognition, like its human counterpart, can benefit from processes such as learning or forgetting, which in spectral signature classification can support adaptive tracking of input nonergodicities. In this paper, we model learning as the acquisition or insertion of a new pattern into a classifier's knowledge base. For example, in neural nets (NNs), this insertion process could correspond to the superposition of a new pattern onto the NN weight matrix. Similarly, we model forgetting as the deletion of a pattern currently stored in the classifier knowledge base, for example, as a pattern deletion operation on the NN weight matrix, which is a difficult goal with classical neural nets (CNNs). In particular, this paper discusses the implementation of feedback control for pattern insertion and deletion in lattice associative memories (LAMs) and dynamically adaptive statistical data fusion (DASDAF) paradigms, in support of signature classification. It is shown that adaptive classifiers based on LNN or DASDAF technology can achieve accurate signature classification in the presence of nonergodic Gaussian and non-Gaussian noise, at low signal-to-noise ratio (SNR). Demonstration involves classification of multiple closely spaced, noise corrupted signatures from a NASA database of space material signatures at SNR > 0.1:1.

  10. Testing Multivariate Adaptive Regression Splines (MARS) as a Method of Land Cover Classification of TERRA-ASTER Satellite Images

    PubMed Central

    Quirós, Elia; Felicísimo, Ángel M.; Cuartero, Aurora

    2009-01-01

    This work proposes a new method to classify multi-spectral satellite images based on multivariate adaptive regression splines (MARS) and compares this classification system with the more common parallelepiped and maximum likelihood (ML) methods. We apply the classification methods to the land cover classification of a test zone located in southwestern Spain. The basis of the MARS method and its associated procedures are explained in detail, and the area under the ROC curve (AUC) is compared for the three methods. The results show that the MARS method provides better results than the parallelepiped method in all cases, and it provides better results than the maximum likelihood method in 13 cases out of 17. These results demonstrate that the MARS method can be used in isolation or in combination with other methods to improve the accuracy of soil cover classification. The improvement is statistically significant according to the Wilcoxon signed rank test. PMID:22291550

  11. Expanding the prevention armamentarium portfolio: A framework for promoting HIV-Conversant Communities within a complex, adaptive epidemiological landscape

    PubMed Central

    Burman, Christopher J.; Aphane, Marota; Mtapuri, Oliver; Delobelle, Peter

    2015-01-01

    Abstract The article describes a design journey that culminated in an HIV-Conversant Community Framework that is now being piloted in the Limpopo Province of South Africa. The objective of the initiative is to reduce the aggregate community viral load by building capacity at multiple scales that strengthens peoples' HIV-related navigational skill sets—while simultaneously opening a ‘chronic situation’ schema. The framework design is based upon a transdisciplinary methodological combination that synthesises ideas and constructs from complexity science and the management sciences as a vehicle through which to re-conceptualise HIV prevention. This resulted in a prototype that included the following constructs: managing HIV-prevention in a complex, adaptive epidemiological landscape; problematising and increasing the scope of the HIV knowledge armamentarium through education that focuses on the viral load and Langerhans cells; disruptive innovation and safe-fail probes followed by the facilitation of path creations and pattern management implementation techniques. These constructs are underpinned by a ‘middle-ground’ prevention approach which is designed to bridge the prevention ‘fault line’, enabling a multi-ontology conceptualisation of the challenge to be developed. The article concludes that stepping outside of the ‘ordered’ epistemological parameters of the existing prevention ‘messaging’ mind-set towards a more systemic approach that emphasises agency, structure and social practices as a contribution to ‘ending AIDS by 2030’ is worthy of further attention if communities are to engage more adaptively with the dynamic HIV landscape in South Africa. PMID:25888256

  12. Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

    PubMed Central

    Abebe, Tiegist D.; Naz, Ali A.; Léon, Jens

    2015-01-01

    Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities. PMID:26483825

  13. Adaptable Neighbours: Movement Patterns of GPS-Collared Leopards in Human Dominated Landscapes in India

    PubMed Central

    Odden, Morten; Athreya, Vidya; Rattan, Sandeep; Linnell, John D. C.

    2014-01-01

    Understanding the nature of the interactions between humans and wildlife is of vital importance for conflict mitigation. We equipped five leopards with GPS-collars in Maharashtra (4) and Himachal Pradesh (1), India, to study movement patterns in human-dominated landscapes outside protected areas. An adult male and an adult female were both translocated 52 km, and exhibited extensive, and directional, post release movements (straight line movements: male  = 89 km in 37 days, female  = 45 km in 5 months), until they settled in home ranges of 42 km2 (male) and 65 km2 (female). The three other leopards, two adult females and a young male were released close to their capture sites and used small home ranges of 8 km2 (male), 11 km2 and 15 km2 (females). Movement patterns were markedly nocturnal, with hourly step lengths averaging 339±9.5 m (SE) during night and 60±4.1 m during day, and night locations were significantly closer to human settlements than day locations. However, more nocturnal movements were observed among those three living in the areas with high human population densities. These visited houses regularly at nighttime (20% of locations <25 m from houses), but rarely during day (<1%). One leopard living in a sparsely populated area avoided human settlements both day and night. The small home ranges of the leopards indicate that anthropogenic food resources may be plentiful although wild prey is absent. The study provides clear insights into the ability of leopards to live and move in landscapes that are extremely modified by human activity. PMID:25390067

  14. Classification.

    PubMed

    Tuxhorn, Ingrid; Kotagal, Prakash

    2008-07-01

    In this article, we review the practical approach and diagnostic relevance of current seizure and epilepsy classification concepts and principles as a basic framework for good management of patients with epileptic seizures and epilepsy. Inaccurate generalizations about terminology, diagnosis, and treatment may be the single most important factor, next to an inadequately obtained history, that determines the misdiagnosis and mismanagement of patients with epilepsy. A stepwise signs and symptoms approach for diagnosis, evaluation, and management along the guidelines of the International League Against Epilepsy and definitions of epileptic seizures and epilepsy syndromes offers a state-of-the-art clinical approach to managing patients with epilepsy.

  15. ADAPT: building conceptual models of the physical and biological processes across permafrost landscapes

    NASA Astrophysics Data System (ADS)

    Allard, M.; Vincent, W. F.; Lemay, M.

    2012-12-01

    Fundamental and applied permafrost research is called upon in Canada in support of environmental protection, economic development and for contributing to the international efforts in understanding climatic and ecological feedbacks of permafrost thawing under a warming climate. The five year "Arctic Development and Adaptation to Permafrost in Transition" program (ADAPT) funded by NSERC brings together 14 scientists from 10 Canadian universities and involves numerous collaborators from academia, territorial and provincial governments, Inuit communities and industry. The geographical coverage of the program encompasses all of the permafrost regions of Canada. Field research at a series of sites across the country is being coordinated. A common protocol for measuring ground thermal and moisture regime, characterizing terrain conditions (vegetation, topography, surface water regime and soil organic matter contents) is being applied in order to provide inputs for designing a general model to provide an understanding of transfers of energy and matter in permafrost terrain, and the implications for biological and human systems. The ADAPT mission is to produce an 'Integrated Permafrost Systems Science' framework that will be used to help generate sustainable development and adaptation strategies for the North in the context of rapid socio-economic and climate change. ADAPT has three major objectives: to examine how changing precipitation and warming temperatures affect permafrost geosystems and ecosystems, specifically by testing hypotheses concerning the influence of the snowpack, the effects of water as a conveyor of heat, sediments, and carbon in warming permafrost terrain and the processes of permafrost decay; to interact directly with Inuit communities, the public sector and the private sector for development and adaptation to changes in permafrost environments; and to train the new generation of experts and scientists in this critical domain of research in Canada

  16. Landscape genetics of plants.

    PubMed

    Holderegger, Rolf; Buehler, Dominique; Gugerli, Felix; Manel, Stéphanie

    2010-12-01

    Landscape genetics is the amalgamation of landscape ecology and population genetics to help with understanding microevolutionary processes such as gene flow and adaptation. In this review, we examine why landscape genetics of plants lags behind that of animals, both in number of studies and consideration of landscape elements. The classical landscape distance/resistance approach to study gene flow is challenging in plants, whereas boundary detection and the assessment of contemporary gene flow are more feasible. By contrast, the new field of landscape genetics of adaptive genetic variation, establishing the relationship between adaptive genomic regions and environmental factors in natural populations, is prominent in plant studies. Landscape genetics is ideally suited to study processes such as migration and adaptation under global change.

  17. Classification

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj C.

    2011-01-01

    A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

  18. Two are better than one: combining landscape genomics and common gardens for detecting local adaptation in forest trees.

    PubMed

    Lepais, Olivier; Bacles, Cecile F

    2014-10-01

    Predicting likely species responses to an alteration of their local environment is key to decision-making in resource management, ecosystem restoration and biodiversity conservation practice in the face of global human-induced habitat disturbance. This is especially true for forest trees which are a dominant life form on Earth and play a central role in supporting diverse communities and structuring a wide range of ecosystems. In Europe, it is expected that most forest tree species will not be able to migrate North fast enough to follow the estimated temperature isocline shift given current predictions for rapid climate warming. In this context, a topical question for forest genetics research is to quantify the ability for tree species to adapt locally to strongly altered environmental conditions (Kremer et al. ). Identifying environmental factors driving local adaptation is, however, a major challenge for evolutionary biology and ecology in general but is particularly difficult in trees given their large individual and population size and long generation time. Empirical evaluation of local adaptation in trees has traditionally relied on fastidious long-term common garden experiments (provenance trials) now supplemented by reference genome sequence analysis for a handful of economically valuable species. However, such resources have been lacking for most tree species despite their ecological importance in supporting whole ecosystems. In this issue of Molecular Ecology, De Kort et al. () provide original and convincing empirical evidence of local adaptation to temperature in black alder, Alnus glutinosa L. Gaertn, a surprisingly understudied keystone species supporting riparian ecosystems. Here, De Kort et al. () use an innovative empirical approach complementing state-of-the-art landscape genomics analysis of A. glutinosa populations sampled in natura across a regional climate gradient with phenotypic trait assessment in a common garden experiment (Fig. ). By

  19. Image classification with densely sampled image windows and generalized adaptive multiple kernel learning.

    PubMed

    Yan, Shengye; Xu, Xinxing; Xu, Dong; Lin, Stephen; Li, Xuelong

    2015-03-01

    We present a framework for image classification that extends beyond the window sampling of fixed spatial pyramids and is supported by a new learning algorithm. Based on the observation that fixed spatial pyramids sample a rather limited subset of the possible image windows, we propose a method that accounts for a comprehensive set of windows densely sampled over location, size, and aspect ratio. A concise high-level image feature is derived to effectively deal with this large set of windows, and this higher level of abstraction offers both efficient handling of the dense samples and reduced sensitivity to misalignment. In addition to dense window sampling, we introduce generalized adaptive l(p)-norm multiple kernel learning (GA-MKL) to learn a robust classifier based on multiple base kernels constructed from the new image features and multiple sets of prelearned classifiers from other classes. With GA-MKL, multiple levels of image features are effectively fused, and information is shared among different classifiers. Extensive evaluation on benchmark datasets for object recognition (Caltech256 and Caltech101) and scene recognition (15Scenes) demonstrate that the proposed method outperforms the state-of-the-art under a broad range of settings.

  20. Classification and assessment of water bodies as adaptive structural measures for flood risk management planning.

    PubMed

    McMinn, William R; Yang, Qinli; Scholz, Miklas

    2010-09-01

    Severe rainfall events have become increasingly common in Europe. Flood defence engineering works are highly capital intensive and can be limited by land availability, leaving land and communities exposed to repeated flooding. Any adaptive drainage structure must have engineered inlets and outlets that control the water level and the rate of release. In Scotland, there are a relatively high number of drinking water reservoirs (operated by Scottish Water), which fall within this defined category and could contribute to flood management control. Reducing the rate of runoff from the upper reaches of a catchment will reduce the volume and peak flows of flood events downstream, thus allowing flood defences to be reduced in size, decreasing the corresponding capital costs. A database of retention basins with flood control potential has been developed for Scotland. The research shows that the majority of small and former drinking water reservoirs are kept full and their spillways are continuously in operation. Utilising some of the available capacity to contribute to flood control could reduce the costs of complying with the EU Flood Directive. Furthermore, the application of a previously developed classification model for Baden in Germany for the Scottish data set showed a lower diversity for basins in Scotland due to less developed infrastructure. The principle value of this approach is a clear and unambiguous categorisation, based on standard variables, which can help to promote communication and understanding between stakeholders.

  1. Classification of hyperspectral urban data using adaptive simultaneous orthogonal matching pursuit

    NASA Astrophysics Data System (ADS)

    Zou, Jinyi; Li, Wei; Huang, Xin; Du, Qian

    2014-01-01

    Simultaneous orthogonal matching pursuit (SOMP) has been recently developed for hyperspectral image classification. It utilizes a joint sparsity model with the assumption that each pixel can be represented by a linear combination of labeled samples. We present an approach to improve the performance of SOMP based on a priori segmentation map. According to the map, we first build a local region where within-segment pixels are preserved while between-segment pixels are excluded. Hyperspectral pixels in the preserved region around the test pixel are then simultaneously represented by a linear combination of training samples, whose weights are recovered by solving a sparsity-constrained optimization problem. Finally, the label of the test pixel is determined to be the class that yields the minimal total residuals between the test samples and the approximations. Experimental results demonstrate that the proposed adaptive SOMP (ASOMP) is superior to some existing classifiers, such as the original SOMP and the recently proposed weighted-SOMP (WSOMP). For example, the ASOMP performed with an accuracy of 95.53% for the ROSIS University of Pavia data with 120 training samples per class, while SOMP obtained an accuracy of 87.61%, an improvement of approximately 8%.

  2. Dynamic transition of transcription and chromatin landscape during fission yeast adaptation to glucose starvation.

    PubMed

    Oda, Arisa; Takemata, Naomichi; Hirata, Yoshito; Miyoshi, Tomoichiro; Suzuki, Yutaka; Sugano, Sumio; Ohta, Kunihiro

    2015-05-01

    Shortage of glucose, the primary energy source for all organisms, is one of the most critical stresses influencing cell viability. Glucose starvation promptly induces changes in mRNA and noncoding RNA (ncRNA) transcription. We previously reported that glucose starvation induces long ncRNA (lncRNA) transcription in the 5' segment of a fission yeast gluconeogenesis gene (fbp1+), which leads to stepwise chromatin alteration around the fbp1+ promoter and to subsequent robust gene activation. Here, we analyzed genomewide transcription by strand-specific RNA sequencing, together with chromatin landscape by immunoprecipitation sequencing (ChIP-seq). Clustering analysis showed that distinct mRNAs and ncRNAs are induced at the early, middle and later stages of cellular response to glucose starvation. The starvation-induced transcription depends substantially on the stress-responsive transcription factor Atf1. Using a new computer program that examines dynamic changes in expression patterns, we identified ncRNAs with similar behavior to the fbp1+ lncRNA. We confirmed that there are continuous lncRNAs associated with local reduction of histone density. Overlapping with the regions for transcription of these lncRNAs, antisense RNAs are antagonistically transcribed under glucose-rich conditions. These results suggest that Atf1-dependent integrated networks of mRNA and lncRNA govern drastic changes in cell physiology in response to glucose starvation.

  3. An analysis of historic and projected climate scenarios in the Western United States using hydrologic landscape classification.

    EPA Science Inventory

    : Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, a...

  4. An analysis of historic and projected climate scenarios in the Western united States using hydrologic landscape classification

    EPA Science Inventory

    Identifying areas of similar hydrology within the United States and its regions (Hydrologic landscapes - HLs) is an active area of research. HLs have been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the ...

  5. Key landscape ecology metrics for assessing climate change adaptation options: rate of change and patchiness of impacts

    USGS Publications Warehouse

    López-Hoffman, Laura; Breshears, David D.; Allen, Craig D.; Miller, Marc L.

    2013-01-01

    Under a changing climate, devising strategies to help stakeholders adapt to alterations to ecosystems and their services is of utmost importance. In western North America, diminished snowpack and river flows are causing relatively gradual, homogeneous (system-wide) changes in ecosystems and services. In addition, increased climate variability is also accelerating the incidence of abrupt and patchy disturbances such as fires, floods and droughts. This paper posits that two key variables often considered in landscape ecology—the rate of change and the degree of patchiness of change—can aid in developing climate change adaptation strategies. We use two examples from the “borderland” region of the southwestern United States and northwestern Mexico. In piñon-juniper woodland die-offs that occurred in the southwestern United States during the 2000s, ecosystem services suddenly crashed in some parts of the system while remaining unaffected in other locations. The precise timing and location of die-offs was uncertain. On the other hand, slower, homogeneous change, such as the expected declines in water supply to the Colorado River delta, will likely impact the entire ecosystem, with ecosystem services everywhere in the delta subject to alteration, and all users likely exposed. The rapidity and spatial heterogeneity of faster, patchy climate change exemplified by tree die-off suggests that decision-makers and local stakeholders would be wise to operate under a Rawlsian “veil of ignorance,” and implement adaptation strategies that allow ecosystem service users to equitably share the risk of sudden loss of ecosystem services before actual ecosystem changes occur. On the other hand, in the case of slower, homogeneous, system-wide impacts to ecosystem services as exemplified by the Colorado River delta, adaptation strategies can be implemented after the changes begin, but will require a fundamental rethinking of how ecosystems and services are used and valued. In

  6. A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification.

    PubMed

    Li, Pu; Chen, Bing; Li, Zelin; Zheng, Xiao; Wu, Hongjing; Jing, Liang; Lee, Kenneth

    2014-09-15

    In this paper, a Monte Carlo simulation based two-stage adaptive resonance theory mapping (MC-TSAM) model was developed to classify a given site into distinguished zones representing different levels of offshore Oil Spill Vulnerability Index (OSVI). It consisted of an adaptive resonance theory (ART) module, an ART Mapping module, and a centroid determination module. Monte Carlo simulation was integrated with the TSAM approach to address uncertainties that widely exist in site conditions. The applicability of the proposed model was validated by classifying a large coastal area, which was surrounded by potential oil spill sources, based on 12 features. Statistical analysis of the results indicated that the classification process was affected by multiple features instead of one single feature. The classification results also provided the least or desired number of zones which can sufficiently represent the levels of offshore OSVI in an area under uncertainty and complexity, saving time and budget in spill monitoring and response.

  7. Who runs fastest in an adaptive landscape: sexual versus asexual reproduction

    NASA Astrophysics Data System (ADS)

    Holmström, Kerstin; Jensen, Henrik Jeldtoft

    2004-06-01

    We compare the speed with which a sexual, respectively, an asexual, population is able to respond to a biased selective pressure. Our model focuses on the Weismann hypothesis that the extra variation caused by crossing-over and recombination during sexual reproduction allows a sexual population to adapt faster. We find, however, that the extra variation amongst the progeny produced during sexual reproduction for most model parameters is unable to overcome the effect that parents with a high individual fitness in general must mate with individuals of lower individual fitness resulting in a moderate reproductive fitness for the pair.

  8. Adaptive training using an artificial neural network and EEG metrics for within- and cross-task workload classification.

    PubMed

    Baldwin, Carryl L; Penaranda, B N

    2012-01-02

    Adaptive training using neurophysiological measures requires efficient classification of mental workload in real time as a learner encounters new and increasingly difficult levels of tasks. Previous investigations have shown that artificial neural networks (ANNs) can accurately classify workload, but only when trained on neurophysiological exemplars from experienced operators on specific tasks. The present study examined classification accuracies for ANNs trained on electroencephalographic (EEG) activity recorded while participants performed the same (within task) and different (cross) tasks for short periods of time with little or no prior exposure to the tasks. Participants performed three working memory tasks at two difficulty levels with order of task and difficulty level counterbalanced. Within-task classification accuracies were high when ANNs were trained on exemplars from the same task or a set containing the to-be-classified task, (M=87.1% and 85.3%, respectively). Cross-task classification accuracies were significantly lower (average 44.8%) indicating consistent systematic misclassification for certain tasks in some individuals. Results are discussed in terms of their implications for developing neurophysiologically driven adaptive training platforms.

  9. Classification of short-lived objects using an interactive adaptable assistance system

    NASA Astrophysics Data System (ADS)

    El Bekri, Nadia; Angele, Susanne; Peinsipp-Byma, Elisabeth

    2015-05-01

    "Although we know that it is not a familiar object, after a while we can say what it resembles". The core task of an aerial image analyst is to recognize different object types based on certain clearly classified characteristics from aerial or satellite images. An interactive recognition assistance system compares selected features with a fixed set of reference objects (core data set). Therefore it is mainly designed to evaluate durable single objects like a specific type of ship or vehicle. Aerial image analysts on missions realized a changed warfare over the time. The task was not anymore to classify and thereby recognize a single durable object. The problem was that they had to classify strong variable objects and the reference set did not match anymore. In order to approach this new scope we introduce a concept to a further development of the interactive assistance system to be able to handle also short-lived, not clearly classifiable and strong variable objects like for example dhows. Dhows are the type of ships that are often used during pirate attacks at the coast of West Africa. Often these ships were build or extended by the pirates themselves. They follow no particular pattern as the standard construction of a merchant ship. In this work we differ between short-lived and durable objects. The interactive adaptable assistance system is supposed to assist image analysts with the classification of objects, which are new and not listed in the reference set of objects yet. The human interaction and perception is an important factor in order to realize this task and achieve the goal of recognition. Therefore we had to model the possibility to classify short-lived objects with appropriate procedures taking into consideration all aspects of short-lived objects. In this paper we will outline suitable measures and the possibilities to categorize short-lived objects via simple basic shapes as well as a temporary data storage concept for shortlived objects. The

  10. Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

    PubMed Central

    Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

    2012-01-01

    Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

  11. Adaptation of neurological practice and policy to a changing US health-care landscape.

    PubMed

    Gorelick, Philip B

    2016-04-01

    Health care in the USA is undergoing a drastic transformation under the Patient Protection and Affordable Care Act. The Patient Protection and Affordable Care Act is driving major health-care policy changes by connecting payment for traditional health-care services to value-based care initiatives and emphasising population health and innovative mechanisms to deliver care. Under the Patient Protection and Affordable Care Act, neurological practice will need to adapt and transform. Therefore, neurological policy should consider employing a new framework for neurological residency training, developing interdisciplinary team approaches to neurological subspecialty care, and strengthening the primary care-neurological specialty care interface to avoid redundancies and other medical waste. Additionally, neurological policy will need to support a more robust review of diagnostic and care pathway use to reduce avoidable expenditures, and test and implement bundled payments for key neurological diagnoses. In view of an anticipated 19% shortage of US neurologists in the next 10 years, development of new neurological policy under the Patient Protection and Affordable Care Act is paramount.

  12. Field heritability of a plant adaptation to fire in heterogeneous landscapes.

    PubMed

    Castellanos, M C; González-Martínez, S C; Pausas, J G

    2015-11-01

    The strong association observed between fire regimes and variation in plant adaptations to fire suggests a rapid response to fire as an agent of selection. It also suggests that fire-related traits are heritable, a precondition for evolutionary change. One example is serotiny, the accumulation of seeds in unopened fruits or cones until the next fire, an important strategy for plant population persistence in fire-prone ecosystems. Here, we evaluate the potential of this trait to respond to natural selection in its natural setting. For this, we use a SNP marker approach to estimate genetic variance and heritability of serotiny directly in the field for two Mediterranean pine species. Study populations were large and heterogeneous in climatic conditions and fire regime. We first estimated the realized relatedness among trees from genotypes, and then partitioned the phenotypic variance in serotiny using Bayesian animal models that incorporated environmental predictors. As expected, field heritability was smaller (around 0.10 for both species) than previous estimates under common garden conditions (0.20). An estimate on a subset of stands with more homogeneous environmental conditions was not different from that in the complete set of stands, suggesting that our models correctly captured the environmental variation at the spatial scale of the study. Our results highlight the importance of measuring quantitative genetic parameters in natural populations, where environmental heterogeneity is a critical aspect. The heritability of serotiny, although not high, combined with high phenotypic variance within populations, confirms the potential of this fire-related trait for evolutionary change in the wild.

  13. The population genomic landscape of human genetic structure, admixture history and local adaptation in Peninsular Malaysia.

    PubMed

    Deng, Lian; Hoh, Boon Peng; Lu, Dongsheng; Fu, Ruiqing; Phipps, Maude E; Li, Shilin; Nur-Shafawati, Ab Rajab; Hatin, Wan Isa; Ismail, Endom; Mokhtar, Siti Shuhada; Jin, Li; Zilfalil, Bin Alwi; Marshall, Christian R; Scherer, Stephen W; Al-Mulla, Fahd; Xu, Shuhua

    2014-09-01

    Peninsular Malaysia is a strategic region which might have played an important role in the initial peopling and subsequent human migrations in Asia. However, the genetic diversity and history of human populations--especially indigenous populations--inhabiting this area remain poorly understood. Here, we conducted a genome-wide study using over 900,000 single nucleotide polymorphisms (SNPs) in four major Malaysian ethnic groups (MEGs; Malay, Proto-Malay, Senoi and Negrito), and made comparisons of 17 world-wide populations. Our data revealed that Peninsular Malaysia has greater genetic diversity corresponding to its role as a contact zone of both early and recent human migrations in Asia. However, each single Orang Asli (indigenous) group was less diverse with a smaller effective population size (N(e)) than a European or an East Asian population, indicating a substantial isolation of some duration for these groups. All four MEGs were genetically more similar to Asian populations than to other continental groups, and the divergence time between MEGs and East Asian populations (12,000--6,000 years ago) was also much shorter than that between East Asians and Europeans. Thus, Malaysian Orang Asli groups, despite their significantly different features, may share a common origin with the other Asian groups. Nevertheless, we identified traces of recent gene flow from non-Asians to MEGs. Finally, natural selection signatures were detected in a batch of genes associated with immune response, human height, skin pigmentation, hair and facial morphology and blood pressure in MEGs. Notable examples include SYN3 which is associated with human height in all Orang Asli groups, a height-related gene (PNPT1) and two blood pressure-related genes (CDH13 and PAX5) in Negritos. We conclude that a long isolation period, subsequent gene flow and local adaptations have jointly shaped the genetic architectures of MEGs, and this study provides insight into the peopling and human migration

  14. Shifting adaptive landscapes: progress and challenges in reconstructing early hominid environments.

    PubMed

    Kingston, John D

    2007-01-01

    Since Darwin situated humans in an evolutionary framework, much discussion has focused on environmental factors that may have shaped or influenced the course of human evolution. Developing adaptive or causal perspectives on the morphological and behavioral variability documented in the human fossil record requires establishing a comprehensive paleoenvironmental context. Reconstructing environments in the past, however, is a complex undertaking, requiring assimilation of diverse datasets of varying quality, scale, and relevance. In response to these difficulties, human evolution has traditionally been interpreted in a somewhat generalized framework, characterized primarily by increasing aridity and seasonality periodically punctuated by pulses or intervals of environmental change, inferred largely from global climatic records. Although these broad paradigms provide useful heuristic approaches for interpreting human evolution, the spatiotemporal resolution remains far too coarse to develop unambiguous causal links. This challenge has become more acute as the emerging paleoenvironmental evidence from equatorial Africa is revealing a complex pattern of habitat heterogeneity and persistent ecological flux throughout the interval of human evolution. In addition, recent discoveries have revealed significant taxonomic diversity and substantially increased the geographic and temporal range of early hominids. These findings raise further questions regarding the role of the environment in mediating or directing the course of human evolution. As a consequence, it is imperative to critically assess the environmental criteria on which many theories and hypotheses of human evolution hinge. The goals here are to 1) compile, review, and evaluate relevant paleoecological datasets from equatorial Africa spanning the last 10 Ma, 2) develop a hierarchical perspective for developing and evaluating hypotheses linking paleoecology to patterns and processes in early hominid evolution, and

  15. Adaptive Neuro-Fuzzy Inference System for Classification of Background EEG Signals from ESES Patients and Controls

    PubMed Central

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3–9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved. PMID:24790547

  16. Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization.

    PubMed

    Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

    2013-01-01

    Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4.

  17. Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization

    PubMed Central

    Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

    2013-01-01

    Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

  18. FMRI-adaptation to highly-rendered color photographs of animals and manipulable artifacts during a classification task.

    PubMed

    Chouinard, Philippe A; Goodale, Melvyn A

    2012-02-01

    We used fMRI to identify brain areas that adapted to either animals or manipulable artifacts while participants classified highly-rendered color photographs into subcategories. Several key brain areas adapted more strongly to one class of objects compared to the other. Namely, we observed stronger adaptation for animals in the lingual gyrus bilaterally, which are known to analyze the color of objects, and in the right frontal operculum and in the anterior insular cortex bilaterally, which are known to process emotional content. In contrast, the left anterior intraparietal sulcus, which is important for configuring the hand to match the three-dimensional structure of objects during grasping, adapted more strongly to manipulable artifacts. Contrary to what a previous study has found using gray-scale photographs, we did not replicate categorical-specific adaptation in the lateral fusiform gyrus for animals and categorical-specific adaptation in the medial fusiform gyrus for manipulable artifacts. Both categories of objects adapted strongly in the fusiform gyrus without any clear preference in location along its medial-lateral axis. We think that this is because the fusiform gyrus has an important role to play in color processing and hence its responsiveness to color stimuli could be very different than its responsiveness to gray-scale photographs. Nevertheless, on the basis of what we found, we propose that the recognition and subsequent classification of animals may depend primarily on perceptual properties, such as their color, and on their emotional content whereas other factors, such as their function, may play a greater role for classifying manipulable artifacts.

  19. Response and adaptation of grapevine cultivars to hydrological conditions forced by a changing climate in a complex landscape

    NASA Astrophysics Data System (ADS)

    De Lorenzi, Francesca; Bonfante, Antonello; Alfieri, Silvia Maria; Monaco, Eugenia; De Mascellis, Roberto; Manna, Piero; Menenti, Massimo

    2014-05-01

    Soil water availability is one of the main components of the terroir concept, influencing crop yield and fruit composition in grapes. The aim of this work is to analyze some elements of the "natural environment" of terroir (climate and soil) in combination with the intra-specific biodiversity of yield responses of grapevine to water availability. From a reference (1961-90) to a future (2021-50) climate case, the effects of climate evolution on soil water availability are assessed and, regarding soil water regime as a predictor variable, the potential spatial distribution of wine-producing cultivars is determined. In a region of Southern Italy (Valle Telesina, 20,000 ha), where a terroir classification has been produced (Bonfante et al., 2011), we applied an agro-hydrological model to determine water availability indicators. Simulations were performed in 60 soil typological units, over the entire study area, and water availability (= hydrological) indicators were determined. Two climate cases were considered: reference (1961-90) and future (2021-2050), the former from climatic statistics on observed variables, and the latter from statistical downscaling of predictions by general circulation models (AOGCM) under A1B SRES scenario. Climatic data consist of daily time series of maximum and minimum temperature, and daily rainfall on a grid with a spatial resolution of 35 km. Spatial and temporal variability of hydrological indicators was addressed. With respect to temporal variability, both inter-annual and intra-annual (i.e. at different stages of crop cycle) variability were analyzed. Some cultivar-specific relations between hydrological indicators and characteristics of must quality were established. Moreover, for several wine-producing cultivars, hydrological requirements were determined by means of yield response functions to soil water availability, through the re-analysis of experimental data derived from scientific literature. The standard errors of estimated

  20. Methods for improving accuracy and extending results beyond periods covered by traditional ground-truth in remote sensing classification of a complex landscape

    NASA Astrophysics Data System (ADS)

    Mueller-Warrant, George W.; Whittaker, Gerald W.; Banowetz, Gary M.; Griffith, Stephen M.; Barnhart, Bradley L.

    2015-06-01

    Successful development of approaches to quantify impacts of diverse landuse and associated agricultural management practices on ecosystem services is frequently limited by lack of historical and contemporary landuse data. We hypothesized that ground truth data from one year could be used to extrapolate previous or future landuse in a complex landscape where cropping systems do not generally change greatly from year to year because the majority of crops are established perennials or the same annual crops grown on the same fields over multiple years. Prior to testing this hypothesis, it was first necessary to classify 57 major landuses in the Willamette Valley of western Oregon from 2005 to 2011 using normal same year ground-truth, elaborating on previously published work and traditional sources such as Cropland Data Layers (CDL) to more fully include minor crops grown in the region. Available remote sensing data included Landsat, MODIS 16-day composites, and National Aerial Imagery Program (NAIP) imagery, all of which were resampled to a common 30 m resolution. The frequent presence of clouds and Landsat7 scan line gaps forced us to conduct of series of separate classifications in each year, which were then merged by choosing whichever classification used the highest number of cloud- and gap-free bands at any given pixel. Procedures adopted to improve accuracy beyond that achieved by maximum likelihood pixel classification included majority-rule reclassification of pixels within 91,442 Common Land Unit (CLU) polygons, smoothing and aggregation of areas outside the CLU polygons, and majority-rule reclassification over time of forest and urban development areas. Final classifications in all seven years separated annually disturbed agriculture, established perennial crops, forest, and urban development from each other at 90 to 95% overall 4-class validation accuracy. In the most successful use of subsequent year ground-truth data to classify prior year landuse, an

  1. Necessity to adapt land use and land cover classification systems to readily accept radar data

    NASA Technical Reports Server (NTRS)

    Drake, B.

    1977-01-01

    A hierarchial, four level, standardized system for classifying land use/land cover primarily from remote-sensor data (USGS system) is described. The USGS system was developed for nonmicrowave imaging sensors such as camera systems and line scanners. The USGS system is not compatible with the land use/land cover classifications at different levels that can be made from radar imagery, and particularly from synthetic-aperture radar (SAR) imagery. The use of radar imagery for classifying land use/land cover at different levels is discussed, and a possible revision of the USGS system to more readily accept land use/land cover classifications from radar imagery is proposed.

  2. Travelling in the eastern Mediterranean with landscape character assessment

    NASA Astrophysics Data System (ADS)

    Abu Jaber, N.; Abunnasr, Y.; Abu Yahya, A.; Boulad, N.; Christou, O.; Dimitropoulos, G.; Dimopoulos, T.; Gkoltsiou, K.; Khreis, N.; Manolaki, P.; Michael, K.; Odeh, T.; Papatheodoulou, A.; Sorotou, A.; Sinno, S.; Suliman, O.; Symons, N.; Terkenli, T.; Trigkas, Vassilis; Trovato, M. G.; Victora, M.; Zomeni, M.; Vogiatzakis, I. N.

    2015-06-01

    Following its application in Northern Europe, Landscape Character Assessment has also been implemented in Euro-Mediterranean countries as a tool for classifying, describing and assessing landscapes. Many landscape classifications employed in the Euro-Mediterranean area are similar in philosophy and application to the ones developed in Northern Europe. However, many aspects of landform, climate, land-use and ecology, as well as socio-economic context are distinctive of Mediterranean landscapes. The paper discusses the conceptual and methodological issues faced during landscape mapping and characterisation in four East-Mediterranean countries (within the MEDSCAPES project): Cyprus, Greece, Jordan and Lebanon. The major hurdles to overcome during the first phase of methodology development include variation in availability, quality, scale and coverage of spatial datasets between countries and also terminology semantics around landscapes. For example, the concept of landscape - a well-defined term in Greek and English - did not exist in Arabic. Another issue is the use of relative terms like 'high mountains,' `uplands' `lowlands' or ' hills'. Such terms, which are regularly used in landscape description, were perceived slightly differently in the four participating countries. In addition differences exist in nomenclature and classification systems used by each country for the dominant landscape-forming factors i.e. geology, soils and land use- but also in the cultural processes shaping the landscapes - compared both to each other and to the Northern-European norms. This paper argues for the development of consistent, regionally adapted, relevant and standardised methodologies if the results and application of LCA in the eastern Mediterranean region are to be transferable and comparable between countries.

  3. Evolution at ‘Sutures’ and ‘Centers’: Recombination Can Aid Adaptation of Spatially Structured Populations on Rugged Fitness Landscapes

    PubMed Central

    Cooper, Jacob D.; Kerr, Benjamin

    2016-01-01

    Epistatic interactions among genes can give rise to rugged fitness landscapes, in which multiple “peaks” of high-fitness allele combinations are separated by “valleys” of low-fitness genotypes. How populations traverse rugged fitness landscapes is a long-standing question in evolutionary biology. Sexual reproduction may affect how a population moves within a rugged fitness landscape. Sex may generate new high-fitness genotypes by recombination, but it may also destroy high-fitness genotypes by shuffling the genes of a fit parent with a genetically distinct mate, creating low-fitness offspring. Either of these opposing aspects of sex require genotypic diversity in the population. Spatially structured populations may harbor more diversity than well-mixed populations, potentially amplifying both positive and negative effects of sex. On the other hand, spatial structure leads to clumping in which mating is more likely to occur between like types, diminishing the effects of recombination. In this study, we use computer simulations to investigate the combined effects of recombination and spatial structure on adaptation in rugged fitness landscapes. We find that spatially restricted mating and offspring dispersal may allow multiple genotypes inhabiting suboptimal peaks to coexist, and recombination at the “sutures” between the clusters of these genotypes can create genetically novel offspring. Sometimes such an offspring genotype inhabits a new peak on the fitness landscape. In such a case, spatially restricted mating allows this fledgling subpopulation to avoid recombination with distinct genotypes, as mates are more likely to be the same genotype. Such population “centers” can allow nascent peaks to establish despite recombination. Spatial structure may therefore allow an evolving population to enjoy the creative side of sexual recombination while avoiding its destructive side. PMID:27973606

  4. Dynamic Learner Profiling and Automatic Learner Classification for Adaptive E-Learning Environment

    ERIC Educational Resources Information Center

    Premlatha, K. R.; Dharani, B.; Geetha, T. V.

    2016-01-01

    E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…

  5. Crop classification by forward neural network with adaptive chaotic particle swarm optimization.

    PubMed

    Zhang, Yudong; Wu, Lenan

    2011-01-01

    This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10(-7) s.

  6. Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm Optimization

    PubMed Central

    Zhang, Yudong; Wu, Lenan

    2011-01-01

    This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10−7 s. PMID:22163872

  7. Improved Correlation of the Neuropathologic Classification According to Adapted World Health Organization Classification and Outcome After Radiotherapy in Patients With Atypical and Anaplastic Meningiomas

    SciTech Connect

    Combs, Stephanie E.; Schulz-Ertner, Daniela; Debus, Juergen; Deimling, Andreas von; Hartmann, Christian

    2011-12-01

    Purpose: To evaluate the correlation between the 1993 and 2000/2007 World Health Organization (WHO) classification with the outcome in patients with high-grade meningiomas. Patients and Methods: Between 1985 and 2004, 73 patients diagnosed with atypical or anaplastic meningiomas were treated with radiotherapy. Sections from the paraffin-embedded tumor material from 66 patients (90%) from 13 different pathology departments were re-evaluated according to the first revised WHO classification from 1993 and the revised classifications from 2000/2007. In 4 cases, the initial diagnosis meningioma was not reproducible (5%). Therefore, 62 patients with meningiomas were analyzed. Results: All 62 tumors were reclassified according to the 1993 and 2000/2007 WHO classification systems. Using the 1993 system, 7 patients were diagnosed with WHO grade I meningioma (11%), 23 with WHO grade II (37%), and 32 with WHO grade III meningioma (52%). After scoring using the 2000/2007 system, we found 17 WHO grade I meningiomas (27%), 32 WHO grade II meningiomas (52%), and 13 WHO grade III meningiomas (21%). According to the 1993 classification, the difference in overall survival was not statistically significant among the histologic subgroups (p = .96). Using the 2000/2007 WHO classifications, the difference in overall survival became significant (p = .02). Of the 62 reclassified patients 29 developed tumor progression (47%). No difference in progression-free survival was observed among the histologic subgroups (p = .44). After grading according to the 2000/2007 WHO classifications, significant differences in progression-free survival were observed among the three histologic groups (p = .005). Conclusion: The new 2000/2007 WHO classification for meningiomas showed an improved correlation between the histologic grade and outcome. This classification therefore provides a useful basis to determine the postoperative indication for radiotherapy. According to our results, a comparison of the

  8. The 'Functional Landscape Approach': Building a socio-ecological evidence base for its contribution to adaptation and resilience in wetland catchments.

    NASA Astrophysics Data System (ADS)

    Carrie, Rachael; Dixon, Alan

    2015-04-01

    Sustainable land management is increasingly taking a landscape approach to advocate simultaneously for local and multiple stakeholder-negotiated development and environmental objectives. Landscape approaches advance earlier frameworks that failed to acknowledge or reconcile either biodiversity or societal trade-offs, and that often tended toward externally-derived or imposed management interventions. Most recently, the management of land to balance biodiversity, food security and ecosystem services outcomes has been informed by socio-ecological systems thinking that seeks to promote an interdisciplinary understanding of any given 'landscape' where environmental and social factors continually interact in complex, adaptive and resilient ways. Reflecting these concepts, and integrating local and external scientific knowledge, the Functional Landscape Approach (FLA) was developed by Wetland Action, focussing on wetland systems in rural sub-Saharan Africa to contribute to environmentally sensitive and climate resilient strategies for safeguarding essential ecosystem services and improving livelihoods and well-being. In particular, the FLA stresses the ways in which land productivity can be improved through supporting, strengthening or re-establishing functional linkages between wetlands and their catchments and provides a basis for local identification of specific interventions to improve the sustainability of land use. Crucially, it also emphasises the need for community-based institutional support and the importance of incentives through market linkages and value-chain development. In this paper we will describe our experiences of developing and implementing the FLA in Ethiopia, Zambia and Malawi over the past two decades. Drawing on successful and less-successful elements of participatory planning, monitoring and evaluation, and the facilitation of long-term sustainable benefits, we will discuss some of the accomplishments and challenges that can be associated with

  9. Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

    USGS Publications Warehouse

    Hand, Brian K; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

    2016-01-01

    Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

  10. Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics.

    PubMed

    Hand, Brian K; Muhlfeld, Clint C; Wade, Alisa A; Kovach, Ryan P; Whited, Diane C; Narum, Shawn R; Matala, Andrew P; Ackerman, Michael W; Garner, Brittany A; Kimball, John S; Stanford, Jack A; Luikart, Gordon

    2016-02-01

    Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

  11. Adapting to the new radiology landscape: challenges and solutions discussed at the 2014 AMCLC open-microphone sessions.

    PubMed

    Hawkins, C Matthew; Flug, Jonathan A; Metter, Darlene; Strax, Richard; Lozano, Kay Denise Spong; Herrington, William; Applegate, Kimberly E

    2015-02-01

    Every year, multiple open-microphone sessions are hosted at the ACR AMCLC. These sessions allow members of the College to offer opinions, experiences, and questions regarding challenges facing radiologists and the future of the profession. At the 2014 AMCLC, 3 such sessions focused, respectively, on radiology's workforce, the obstacles slowing the shift from volume to value, and alternative reimbursement models and the shifting physician employment landscape. These open-microphone sessions framed contemporary obstacles and emerging challenges that professional radiology societies, such as the ACR, should target with new initiatives and use of resources; in addition, the sessions revealed opportunities for members, councilors, and state chapters to respond with meaningful resolutions and policy proposals.

  12. Functional decoupling between flowers and leaves in the Ameroglossum pernambucense complex can facilitate local adaptation across a pollinator and climatic heterogeneous landscape.

    PubMed

    Wanderley, A M; Galetto, L; Machado, I C S

    2016-03-01

    Decoupling between floral and leaf traits is expected in plants with specialized pollination systems to assure a precise flower-pollinator fit, irrespective of leaf variation associated with environmental heterogeneity (functional modularity). Nonetheless, developmental interactions among floral traits also decouple flowers from leaves regardless of selection pressures (developmental modularity). We tested functional modularity in the hummingbird-pollinated flowers of the Ameroglossum pernambucense complex while controlling for developmental modularity. Using two functional traits responsible for flower-pollinator fit [floral tube length (TL) and anther-nectary distance (AN)], one floral trait not linked to pollination [sepal length (SL), control for developmental modularity] and one leaf trait [leaf length (LL)], we found evidence of flower functional modularity. Covariation between TL and AN was ca. two-fold higher than the covariation of either of these traits with sepal and leaf lengths, and variations in TL and AN, important for a precise flower-pollinator fit, were smaller than SL and LL variations. Furthermore, we show that previously reported among-population variation of flowers associated with local pollinator phenotypes was independent from SL and LL variations. These results suggest that TL and AN are functionally linked to fit pollinators and sufficiently decoupled from developmentally related floral traits (SL) and vegetative traits (LL). These results support previous evidences of population differentiation due to local adaptation in the A. pernambucense complex and shed light on the role of flower-leaf decoupling for local adaptation in species distributed across biotic and abiotic heterogeneous landscapes.

  13. Quasispecies on Fitness Landscapes.

    PubMed

    Schuster, Peter

    2016-01-01

    Selection-mutation dynamics is studied as adaptation and neutral drift on abstract fitness landscapes. Various models of fitness landscapes are introduced and analyzed with respect to the stationary mutant distributions adopted by populations upon them. The concept of quasispecies is introduced, and the error threshold phenomenon is analyzed. Complex fitness landscapes with large scatter of fitness values are shown to sustain error thresholds. The phenomenological theory of the quasispecies introduced in 1971 by Eigen is compared to approximation-free numerical computations. The concept of strong quasispecies understood as mutant distributions, which are especially stable against changes in mutations rates, is presented. The role of fitness neutral genotypes in quasispecies is discussed.

  14. [Landscape and ecological genomics].

    PubMed

    Tetushkin, E Ia

    2013-10-01

    Landscape genomics is the modern version of landscape genetics, a discipline that arose approximately 10 years ago as a combination of population genetics, landscape ecology, and spatial statistics. It studies the effects of environmental variables on gene flow and other microevolutionary processes that determine genetic connectivity and variations in populations. In contrast to population genetics, it operates at the level of individual specimens rather than at the level of population samples. Another important difference between landscape genetics and genomics and population genetics is that, in the former, the analysis of gene flow and local adaptations takes quantitative account of landforms and features of the matrix, i.e., hostile spaces that separate species habitats. Landscape genomics is a part of population ecogenomics, which, along with community genomics, is a major part of ecological genomics. One of the principal purposes of landscape genomics is the identification and differentiation of various genome-wide and locus-specific effects. The approaches and computation tools developed for combined analysis of genomic and landscape variables make it possible to detect adaptation-related genome fragments, which facilitates the planning of conservation efforts and the prediction of species' fate in response to expected changes in the environment.

  15. Phenotypic plasticity of nest timing in a post-glacial landscape: how do reptiles adapt to seasonal time constraints?

    PubMed

    Edge, Christopher B; Rollinson, Njal; Brooks, Ronald J; Congdon, Justin D; Iverson, John B; Janzen, Fredric J; Litzgus, Jacqueline D

    2017-02-01

    Life histories evolve in response to constraints on the time available for growth and development. Nesting date and its plasticity in response to spring temperature may therefore be important components of fitness in oviparous ectotherms near their northern range limit, as reproducing early provides more time for embryos to complete development before winter. We used data collected over several decades to compare air temperature and nest date plasticity in populations of painted turtles and snapping turtles from a relatively warm environment (southeastern Michigan) near the southern extent of the last glacial maximum to a relatively cool environment (central Ontario) near the northern extent of post-glacial recolonization. For painted turtles, population-level differences in reaction norm elevation for two phenological traits were consistent with adaptation to time constraints, but no differences in reaction norm slopes were observed. For snapping turtle populations, the difference in reaction norm elevation for a single phenological trait was in the opposite direction of what was expected under adaptation to time constraints, and no difference in reaction norm slope was observed. Finally, among-individual variation in individual plasticity for nesting date was detected only in the northern population of snapping turtles, suggesting that reaction norms are less canalized in this northern population. Overall, we observed evidence of phenological adaptation, and possibly maladaptation, to time constraints in long-lived reptiles. Where present, (mal)adaptation occurred by virtue of differences in reaction norm elevation, not reaction norm slope. Glacial history, generation time, and genetic constraint may all play an important role in the evolution of phenological timing and its plasticity in long-lived reptiles.

  16. Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

    EPA Science Inventory

    Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

  17. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  18. Landscape evolutionary genomics.

    PubMed

    Lowry, David B

    2010-08-23

    Tremendous advances in genetic and genomic techniques have resulted in the capacity to identify genes involved in adaptive evolution across numerous biological systems. One of the next major steps in evolutionary biology will be to determine how landscape-level geographical and environmental features are involved in the distribution of this functional adaptive genetic variation. Here, I outline how an emerging synthesis of multiple disciplines has and will continue to facilitate a deeper understanding of the ways in which heterogeneity of the natural landscapes mould the genomes of organisms.

  19. A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation.

    PubMed

    Joost, S; Bonin, A; Bruford, M W; Després, L; Conord, C; Erhardt, G; Taberlet, P

    2007-09-01

    The detection of adaptive loci in the genome is essential as it gives the possibility of understanding what proportion of a genome or which genes are being shaped by natural selection. Several statistical methods have been developed which make use of molecular data to reveal genomic regions under selection. In this paper, we propose an approach to address this issue from the environmental angle, in order to complement results obtained by population genetics. We introduce a new method to detect signatures of natural selection based on the application of spatial analysis, with the contribution of geographical information systems (GIS), environmental variables and molecular data. Multiple univariate logistic regressions were carried out to test for association between allelic frequencies at marker loci and environmental variables. This spatial analysis method (SAM) is similar to current population genomics approaches since it is designed to scan hundreds of markers to assess a putative association with hundreds of environmental variables. Here, by application to studies of pine weevils and breeds of sheep we demonstrate a strong correspondence between SAM results and those obtained using population genetics approaches. Statistical signals were found that associate loci with environmental parameters, and these loci behave atypically in comparison with the theoretical distribution for neutral loci. The contribution of this new tool is not only to permit the identification of loci under selection but also to establish hypotheses about ecological factors that could exert the selection pressure responsible. In the future, such an approach may accelerate the process of hunting for functional genes at the population level.

  20. Making sense in a complex landscape: how the Cynefin Framework from Complex Adaptive Systems Theory can inform health promotion practice.

    PubMed

    Van Beurden, Eric K; Kia, Annie M; Zask, Avigdor; Dietrich, Uta; Rose, Lauren

    2013-03-01

    Health promotion addresses issues from the simple (with well-known cause/effect links) to the highly complex (webs and loops of cause/effect with unpredictable, emergent properties). Yet there is no conceptual framework within its theory base to help identify approaches appropriate to the level of complexity. The default approach favours reductionism--the assumption that reducing a system to its parts will inform whole system behaviour. Such an approach can yield useful knowledge, yet is inadequate where issues have multiple interacting causes, such as social determinants of health. To address complex issues, there is a need for a conceptual framework that helps choose action that is appropriate to context. This paper presents the Cynefin Framework, informed by complexity science--the study of Complex Adaptive Systems (CAS). It introduces key CAS concepts and reviews the emergence and implications of 'complex' approaches within health promotion. It explains the framework and its use with examples from contemporary practice, and sets it within the context of related bodies of health promotion theory. The Cynefin Framework, especially when used as a sense-making tool, can help practitioners understand the complexity of issues, identify appropriate strategies and avoid the pitfalls of applying reductionist approaches to complex situations. The urgency to address critical issues such as climate change and the social determinants of health calls for us to engage with complexity science. The Cynefin Framework helps practitioners make the shift, and enables those already engaged in complex approaches to communicate the value and meaning of their work in a system that privileges reductionist approaches.

  1. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  2. Hydrologic Landscape Characterization for the Pacific Northwest, USA

    EPA Science Inventory

    Hydrologic classification can help address some of the challenges facing catchment hydrology. Wigington et al. (2013) developed a hydrologic landscape (HL) approach to classification that was applied to the state of Oregon. Several characteristics limited its applicability outs...

  3. Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

    USGS Publications Warehouse

    Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

    2010-01-01

    Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

  4. Dysregulation of innate and adaptive serum mediators precedes systemic lupus erythematosus classification and improves prognostic accuracy of autoantibodies.

    PubMed

    Lu, Rufei; Munroe, Melissa E; Guthridge, Joel M; Bean, Krista M; Fife, Dustin A; Chen, Hua; Slight-Webb, Samantha R; Keith, Michael P; Harley, John B; James, Judith A

    2016-11-01

    Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a poorly understood preclinical stage of immune dysregulation and symptom accrual. Accumulation of antinuclear autoantibody (ANA) specificities is a hallmark of impending clinical disease. Yet, many ANA-positive individuals remain healthy, suggesting that additional immune dysregulation underlies SLE pathogenesis. Indeed, we have recently demonstrated that interferon (IFN) pathways are dysregulated in preclinical SLE. To determine if other forms of immune dysregulation contribute to preclinical SLE pathogenesis, we measured SLE-associated autoantibodies and soluble mediators in samples from 84 individuals collected prior to SLE classification (average timespan = 5.98 years), compared to unaffected, healthy control samples matched by race, gender, age (±5 years), and time of sample procurement. We found that multiple soluble mediators, including interleukin (IL)-5, IL-6, and IFN-γ, were significantly elevated in cases compared to controls more than 3.5 years pre-classification, prior to or concurrent with autoantibody positivity. Additional mediators, including innate cytokines, IFN-associated chemokines, and soluble tumor necrosis factor (TNF) superfamily mediators increased longitudinally in cases approaching SLE classification, but not in controls. In particular, levels of B lymphocyte stimulator (BLyS) and a proliferation-inducing ligand (APRIL) were comparable in cases and controls until less than 10 months pre-classification. Over the entire pre-classification period, random forest models incorporating ANA and anti-Ro/SSA positivity with levels of IL-5, IL-6, and the IFN-γ-induced chemokine, MIG, distinguished future SLE patients with 92% (±1.8%) accuracy, compared to 78% accuracy utilizing ANA positivity alone. These data suggest that immune dysregulation involving multiple pathways contributes to SLE pathogenesis. Importantly, distinct immunological profiles are predictive for

  5. Why some fitness landscapes are fractal.

    PubMed

    Weinberger, E D; Stadler, P F

    1993-07-21

    Many biological and biochemical measurements, for example the "fitness" of a particular genome, or the binding affinity to a particular substrate, can be treated as a "fitness landscape", an assignment of numerical values to points in sequence space (or some other configuration space). As an alternative to the enormous amount of data required to completely describe such a landscape, we propose a statistical characterization, based on the properties of a random walk through the landscape and, more specifically, its autocorrelation function. Under assumptions roughly satisfied by two classes of simple model landscapes (the N-k model and the p-spin model) and by the landscape of estimated free energies of RNA secondary structures, this autocorrelation function, along with the mean and variance of individual points and the size of the landscape, completely characterize it. Having noted that these and other landscapes of estimated replication and degradation rates all have a well-defined correlation length, we propose a classification of landscapes depending on how the correlation length scales with the diameter of the landscape. The landscapes of some of the kinetic parameters of RNA molecules scale similarly to the model landscapes introduced into evolutionary studies from other fields, such as quadratic spin glasses and the traveling salesman problem, but the correlation length of RNA landscapes are considerably smaller. Nevertheless, both the model and some of the RNA landscapes satisfy a test of self-similarity proposed by Sorkin (1988).

  6. Study of settlement distribution pattern in the Kolkheti lowland (Black Sea coast of Georgia) starting from early Bronze Age - natural and human influence and adaptation to landscape evolution

    NASA Astrophysics Data System (ADS)

    Elashvili, Mikheil; Akhvlediani, Dimitri; Navrozashvili, Levan; Sukhishvili, Lasha; Kirkitadze, Giorgi; Kelterbaum, Daniel; Laermans, Hannes

    2015-04-01

    archaeological datasets are collected in the joint-venture project and in addition with known historical and old topographic maps of the region they represent a good start for the research. There are typical ancient settlements in the Kolkheti lowland, called locally "Dikhagudzuba", which are still identifiable on aerial imagery. Their structure, physical dimensions and locations were analyzed from aerial and on site studies. Data from existing archaeological studies and recent field works were analyzed to create a reliable database on the distribution of Bronze Age settlements. Changes in paleoclimate, sea level and river deltas represent the main components to form a paleolandscape of the study area. Based on the results of recent fieldwork and the analyses of regional historical maps in addition with the general geological and geomorphological settings paleogeographical scenarios were constructed. Proposed models of past landscape changes and human settlement pattern were merged and analyzed. From one hand the human settlement distribution (taking into account tells relation with the local landscape of the same period) help us to identify the best suitable scenario from the set of paleolandscape patterns. Moreover, paleogeographical scenarios provide a better understanding on the erection of human settlements in the past, and their influence and adaptation to ongoing changes.

  7. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    NASA Astrophysics Data System (ADS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-03-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

  8. Adapting Landscape Mosaics of medIteranean Rainfed Agrosystems for a sustainable management of crop production, water and soil resources: the ALMIRA project.

    NASA Astrophysics Data System (ADS)

    Jacob, Frédéric; Mekki, Insaf; Chikhaoui, Mohamed

    2014-05-01

    In the context of mitigating the pressures induced by global change combined with demography and market pressures, there is increasing societal demand and scientific need to understand the functioning of Mediterranean Rainfed Agrosystems (MRAs) for their potential to provide various environmental and economic services of importance such as food production, preservation of employment and local knowhow, downstream water delivery or mitigation of rural exodus. Efficient MRAs management strategies that allow for compromises between economic development and natural resources preservation are needed. Such strategies require innovative system based research, integration across approaches and scales. One of the major challenges is to make all contributions from different disciplines converging towards a reproducible transdisciplinary approach. The objective of this communication is to present the ALMIRA project, a Tunisian - Moroccan - French project which lasts four years (2014 - 2017). The communication details the societal context, the scientific positioning and the related work hypothesis, the study areas, the project structure, the expected outcomes and the partnership which capitalizes on long term collaborations. ALMIRA aims to explore the modulation of landscape mosaics within MRAs to optimize landscape services. To explore this new lever, ALMIRA proposes to design, implement and test a new Integrated Assessment Modelling approach that explicitly i) includes innovations and action means into prospective scenarii for landscape evolutions, and ii) addresses landscape mosaics and processes of interest from the agricultural field to the resource governance catchment. This requires tackling methodological challenges in relation to i) the design of spatially explicit landscape evolution scenarii, ii) the coupling of biophysical processes related to agricultural catchment hydrology, iii) the digital mapping of landscape properties and iv) the economic assessment of the

  9. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

    PubMed

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-12-13

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

  10. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

    PubMed Central

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-01-01

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

  11. Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation

    PubMed Central

    Melnyk, Stepan; James, S. Jill; Hahn, Juergen

    2017-01-01

    The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets. PMID:28301476

  12. Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.

    PubMed

    Howsmon, Daniel P; Kruger, Uwe; Melnyk, Stepan; James, S Jill; Hahn, Juergen

    2017-03-01

    The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets.

  13. Equivalent Diagnostic Classification Models

    ERIC Educational Resources Information Center

    Maris, Gunter; Bechger, Timo

    2009-01-01

    Rupp and Templin (2008) do a good job at describing the ever expanding landscape of Diagnostic Classification Models (DCM). In many ways, their review article clearly points to some of the questions that need to be answered before DCMs can become part of the psychometric practitioners toolkit. Apart from the issues mentioned in this article that…

  14. Mars Landscapes

    NASA Video Gallery

    Spacecraft have studied the Martian surface for decades, giving Earthlings insights into the history, climate and geology of our nearest neighbor, Mars. These images are from "Mars Landscapes," a v...

  15. Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

    NASA Astrophysics Data System (ADS)

    Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

    2016-06-01

    The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

  16. Applying landscape genetics to the microbial world.

    PubMed

    Dudaniec, Rachael Y; Tesson, Sylvie V M

    2016-07-01

    Landscape genetics, which explicitly quantifies landscape effects on gene flow and adaptation, has largely focused on macroorganisms, with little attention given to microorganisms. This is despite overwhelming evidence that microorganisms exhibit spatial genetic structuring in relation to environmental variables. The increasing accessibility of genomic data has opened up the opportunity for landscape genetics to embrace the world of microorganisms, which may be thought of as 'the invisible regulators' of the macroecological world. Recent developments in bioinformatics and increased data accessibility have accelerated our ability to identify microbial taxa and characterize their genetic diversity. However, the influence of the landscape matrix and dynamic environmental factors on microorganism genetic dispersal and adaptation has been little explored. Also, because many microorganisms coinhabit or codisperse with macroorganisms, landscape genomic approaches may improve insights into how micro- and macroorganisms reciprocally interact to create spatial genetic structure. Conducting landscape genetic analyses on microorganisms requires that we accommodate shifts in spatial and temporal scales, presenting new conceptual and methodological challenges not yet explored in 'macro'-landscape genetics. We argue that there is much value to be gained for microbial ecologists from embracing landscape genetic approaches. We provide a case for integrating landscape genetic methods into microecological studies and discuss specific considerations associated with the novel challenges this brings. We anticipate that microorganism landscape genetic studies will provide new insights into both micro- and macroecological processes and expand our knowledge of species' distributions, adaptive mechanisms and species' interactions in changing environments.

  17. Monitoring of Agricultural Landscape in Norway

    NASA Astrophysics Data System (ADS)

    Wallin, H. G.; Engan, G.

    2012-07-01

    An overall societal aim is to ensure a sustainable use and management of agricultural landscapes. This requires continuous delivery of reliable and up-to-date information to decision-makers. To be able to deliver this information, a monitoring program for agricultural landscapes was initiated in Norway 13 years ago. The program documents and reports on land use / land cover changes from data captured through interpretation of true colour aerial photos using stereo instruments. The monitoring programme is based on a sample of 1000 squares of 1 × 1 km and the entire sample of squares is photographed over a five-year period. Each square is then mapped repeatedly every fifth year to record changes. Aerial photo interpretation is based on a custom classification system which is built up hierarchically, with three levels. The first level comprises seven land type classes: Agricultural land, Bare ground, Semi-natural open vegetation, Unforested wetland vegetation, Forest, Urban areas and Water. These land classes are further divided into 24 land types at level two, and approximately 100 land types at level 3. In addition to land type units we map both line elements like stone fences and point elements like buildings and solitary threes. By use of indicators that describe status and change focusing on themes of particular policy interest, we can report on whether policy aims are being fulfilled or not. Four indicator themes have been in focus hitherto: landscape spatial structure, biological diversity, cultural heritage and accessibility. Our data is stored in databases and most of the data quality check/structure process and analyses are now being made in open source software like PostGIS and PostSQL. To assess the accuracy of the photo-interpretation, ground truthing is carried out on 10 % of the squares. The results of this operation document the benefits of having access to photos of the same area from two different years. The program is designed first and foremost to

  18. Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Abreu, Carlos; Miranda, Francisco; Mendes, Paulo M.

    2016-06-01

    The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular, they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless, due to the critical nature of the data conveyed by such patient monitoring applications, they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context, vis-à-vis the quality of service being provided by the wireless sensor network, this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric's value.

  19. Catchment classification by means of hydrological models

    NASA Astrophysics Data System (ADS)

    Hellebrand, Hugo; Ley, Rita; Casper, Markus

    2013-04-01

    An important hydrological objective is catchment classification that will serve as a basis for the regionalisation of discharge parameters or model parameters. The main task of this study is the development and assessment of two classification approaches with respect to their efficiency in catchment classification. The study area in western Germany comprises about 80 catchments that range in size from 8 km2 up to 1500 km2, covering a wide range of geological substrata, soils, landscapes and mean annual precipitation. In a first approach Self Organising Maps (SOMs) use discharge characteristics or catchment characteristics to classify the catchments of the study area. Next, a reference hydrological model calibrates the catchments of the study area and tests the possibilities of parameter transfer. Compared to the transfer of parameters outside a class, for most catchments the model performance improves when parameters within a class are transferred. Thus, it should be possible to distinguish catchment classes by means of a hydrological model. The classification results of the SOM are compared to the classification results of the reference hydrological model in order to determine the latter validity. The second approach builds on the first approach in such a way that it uses the Superflex Modelling Framework instead of only one reference model. Within this framework multiple conceptual model structures can be calibrated and adapted. Input data for each calibration of a catchment are hourly time series of runoff, precipitation and evaporation for at least eight years. The calibration of multiple models for each catchment and their comparison allows for the assessment of the influence of different model structures on model performance. Learning loops analyse model performance and adapt model structures accordingly with a view to performance improvement. The result of the modelling exercise is a best performing model structure for each catchment that serves as a basis

  20. Epigenetic Inheritance across the Landscape

    PubMed Central

    Whipple, Amy V.; Holeski, Liza M.

    2016-01-01

    The study of epigenomic variation at the landscape-level in plants may add important insight to studies of adaptive variation. A major goal of landscape genomic studies is to identify genomic regions contributing to adaptive variation across the landscape. Heritable variation in epigenetic marks, resulting in transgenerational plasticity, can influence fitness-related traits. Epigenetic marks are influenced by the genome, the environment, and their interaction, and can be inherited independently of the genome. Thus, epigenomic variation likely influences the heritability of many adaptive traits, but the extent of this influence remains largely unknown. Here, we summarize the relevance of epigenetic inheritance to ecological and evolutionary processes, and review the literature on landscape-level patterns of epigenetic variation. Landscape-level patterns of epigenomic variation in plants generally show greater levels of isolation by distance and isolation by environment then is found for the genome, but the causes of these patterns are not yet clear. Linkage between the environment and epigenomic variation has been clearly shown within a single generation, but demonstrating transgenerational inheritance requires more complex breeding and/or experimental designs. Transgenerational epigenetic variation may alter the interpretation of landscape genomic studies that rely upon phenotypic analyses, but should have less influence on landscape genomic approaches that rely upon outlier analyses or genome–environment associations. We suggest that multi-generation common garden experiments conducted across multiple environments will allow researchers to understand which parts of the epigenome are inherited, as well as to parse out the relative contribution of heritable epigenetic variation to the phenotype. PMID:27826318

  1. Planning Construction Research of Modern Urban Landscape

    NASA Astrophysics Data System (ADS)

    Xiao, Z. Q.; Chen, W.

    With the development and expansion of the city's traditional urban landscape planning methods have been difficult to adapt to the requirements of modern urban development, in the new urban construction, planning what kind of urban landscape is a new research topic. The article discusses the principles of modern urban landscape planning and development, promote the adoption of new concepts and theories, building more regional characteristics, more humane, more perfect, more emphasis on urban landscape pattern natural ecological protection and construction can sustainable development of urban living environment, and promote the development and construction of the city.

  2. Climates, Landscapes, and Civilizations

    NASA Astrophysics Data System (ADS)

    Schultz, Colin

    2013-10-01

    Humans are now the dominant driver of global climate change. From ocean acidification to sea level rise, changes in precipitation patterns, and rising temperatures, global warming is presenting us with an uncertain future. However, this is not the first time human civilizations have faced a changing world. In the AGU monograph Climates, Landscapes, and Civilizations, editors Liviu Giosan, Dorian Q. Fuller, Kathleen Nicoll, Rowan K. Flad, and Peter C. Clift explore how some ancient peoples weathered the shifting storms while some faded away. In this interview, Eos speaks with Liviu Giosan about the decay of civilizations, ancient adaptation, and the surprisingly long history of humanity's effect on the Earth.

  3. Multi-scale forest landscape pattern characterization

    NASA Astrophysics Data System (ADS)

    Wang, Jialing

    The purpose of this dissertation is to examine several important issues in landscape pattern analysis, including the identification of important landscape metrics, the impact of the modifiable areal unit problem (MAUP) in landscape pattern analysis, the linkage between pattern and process, and the application of landscape pattern analysis. A theoretical framework of hierarchical patch dynamics paradigm and a technical framework of GIS and remote sensing integration are employed to address these questions. The Red Hills region of southwestern Georgia and northern Florida is chosen as the study area. Land use/cover (LULC) and longleaf pine distribution maps were generated through satellite image classification. Sub-watersheds were used as the main analysis units. Principal component analysis (PCA) was conducted on 43 sub-watersheds at three hierarchical LULC levels to identify important landscape metrics. At both landscape- and class-levels, the measurement of fragmentation was identified as the most important landscape dimension. Other dimensions and important metrics varied with different scales. Hexagons were used as an alternative zoning system to examine the MAUP impact in landscape pattern analysis. The results indicated that landscape pattern analyses at class level and at broader scales were more sensitive to MAUP than at landscape level and at finer scales. Local-scale pattern analysis based on moving window analysis greatly reduced the impact of MAUP at class level, but had little effects at landscape level. An examination of the relationship between landscape pattern variables and biophysical/socio-economic variables was undertaken by using statistical analysis. The biophysical variables of soil drainage and mean slope and the socio-economic variables of road density, population density, distance to Tallahassee, Florida, and plantation amount were found to be closely correlated to the landscape patterns in this region. However, a large amount of variation

  4. The association forecasting of 13 variants within seven asthma susceptibility genes on 3 serum IgE groups in Taiwanese population by integrating of adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods.

    PubMed

    Wang, Cheng-Hang; Liu, Baw-Jhiune; Wu, Lawrence Shih-Hsin

    2012-02-01

    Asthma is one of the most common chronic diseases in children. It is caused by complicated coactions between various genetic factors and environmental allergens. The study aims to integrate the concept of implementing adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods for forecasting the association of asthma susceptibility genes on 3 serum IgE groups. The ANFIS model was trained and tested with data sets obtained from 425 asthmatic subjects and 483 non-asthma subjects from the Taiwanese population. We assessed 13 single-nucleotide polymorphisms (SNPs) in seven well-known asthma susceptibility genes; firstly, the proposed ANFIS model learned to reduce input features from the 13 SNPs. And secondly, the classification will be used to classify the serum IgE groups from the simulated SNPs results. The performance of the ANFIS model, classification accuracies and the results confirmed that the integration of ANFIS and classified analysis has potential in association discovery.

  5. Vulnerability of Oregon hydrologic landscapes and streamflow to climate change

    EPA Science Inventory

    Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors. Such assessments could be particularly useful in determining hydrologic vulnerability from climate change. ...

  6. A comparison of grazing behavior between desert adapted Mexican Criollo cattle and temperate british breeds using two diverse landscapes in New Mexico and Chihuahua.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study was designed to test how grazing behaviors differ between desert adapted Mexican criollo cattle and temperate British beef breeds, to learn how each breed interacts with environments common to the southwestern US and northwestern Mexico. Additionally, criollo cattle may be a better breed ...

  7. [Segmentation-based multi-scale urban green space landscape].

    PubMed

    Sun, Xiaofang; Lu, Jian; Sun, Yibin

    2006-09-01

    In this study, three scales urban green space landscapes were generated by multi-resolution segmentation. With 50 and 300 pixels as the object segmentation thresholds, the small- and large-scale landscape object image layers were produced, and the two object image layers were obtained by the nearest neighbor classification method. The result of small-scale landscape classification image was segmented into middle-scale landscape image, and then classified. Green space information was extracted through vector form of object image layers of three scales landscape classification. The landscape indexes diversity, dominance, evenness, fractal dimension, fragmentation, and interior to edge ration were calculated, with the largest values of the former four indexes being 2.2, 0.681, 0.948, and 0.326, and the smallest values being 1.641, 0. 122, 0.707, and 0.113, respectively, indicating that the diversity, evenness and fragmentation decreased, while the dominance increased with increasing landscape scale. The method of multi-resolution segmentation to generate multi-scale landscape could meet the needs of urban green space landscape research.

  8. PESP Landscaping Initiative

    EPA Pesticide Factsheets

    Landscaping practices can positively or negatively affect local environments and human health. The Landscaping Initiative seeks to enhance benefits of landscaping while reducing need for pesticides, fertilizers, etc., by working with partners.

  9. Assessing the habitat suitability of agricultural landscapes for characteristic breeding bird guilds using landscape metrics.

    PubMed

    Borges, Friederike; Glemnitz, Michael; Schultz, Alfred; Stachow, Ulrich

    2017-04-01

    Many of the processes behind the decline of farmland birds can be related to modifications in landscape structure (composition and configuration), which can partly be expressed quantitatively with measurable or computable indices, i.e. landscape metrics. This paper aims to identify statistical relationships between the occurrence of birds and the landscape structure. We present a method that combines two comprehensive procedures: the "landscape-centred approach" and "guild classification". Our study is based on more than 20,000 individual bird observations based on a 4-year bird monitoring approach in a typical agricultural area in the north-eastern German lowlands. Five characteristic bird guilds, each with three characteristic species, are defined for the typical habitat types of that area: farmland, grassland, hedgerow, forest and settlement. The suitability of each sample plot for each guild is indicated by the level of persistence (LOP) of occurrence of three respective species. Thus, the sample plots can be classified as "preferred" or "less preferred" depending on the lower and upper quartiles of the LOP values. The landscape structure is characterized by 16 different landscape metrics expressing various aspects of landscape composition and configuration. For each guild, the three landscape metrics with the strongest rank correlation with the LOP values and that are not mutually dependent were identified. For four of the bird guilds, the classification success was better than 80%, compared with only 66% for the grassland bird guild. A subset of six landscape metrics proved to be the most meaningful and sufficiently classified the sample areas with respect to bird guild suitability. In addition, derived logistic functions allowed the production of guild-specific habitat suitability maps for the whole landscape. The analytical results show that the proposed approach is appropriate to assess the habitat suitability of agricultural landscapes for characteristic

  10. Driving the Landscape

    NASA Astrophysics Data System (ADS)

    Haff, P. K.

    2012-12-01

    destination—whereas the natural evolution of landscape has no such goal. Goals will become an essential feature of landscape prediction. The presence of a goal potentially increases our ability to predict, provided it is possible to use feedback (i.e., management) to nudge the system back in the "right" direction when it starts to stray. Under a regime of accelerating technology the closest we can get to predicting the longer term future of landscape is adaptive management, which at large scale is really geoengineer the system. The goal presumably would be to maintain a condition conducive to human well-being, for example to maintain a suitable fraction of global arable land. A successful "prediction" would be to stay within an envelope of states consistent with that goal. We cannot say, however, in what specific state the landscape will be at any time beyond the near future; this will depend on the future sequence of management decisions, which are, like the system they are managing, unpredictable, except shortly before they are implemented. The landscape of the future will thus likely be the result of a series of quick fixes to previous trends in landscape change. Similar comments apply to the prediction, or management, of climate. There is of course no guarantee that it will be possible to stay within the desired envelope of well-being.

  11. PNW Hydrologic Landscape Class

    EPA Pesticide Factsheets

    Work has been done to expand the hydrologic landscapes (HLs) concept and to develop an approach for using it to address streamflow vulnerability from climate change. This work has included development of the HL classification framework and its application to Oregon, use of the HL classes to predict where a simple lumped hydrologic model accurately predicts daily streamflow, use of HL information to model the presence of cold-water patches at tributary confluences, and combining Oregon HL results with temperature and precipitation predictions to examine how HLs would vary as a result of climate change. As a part of the current work, the HL approach has been expanded to the Pacific Northwest (Oregon, Washington, and Idaho) based on a revision of the approach that makes it more broadly applicable. This revised approach has several advantages compared with the original approach: it is not limited to areas that have an aquifer permeability map; it uses a flexible approach to converting a nationally available geospatial dataset into assessment units; and it is more robust. These improvements should allow the revised HL approach to be applied more often in situations requiring hydrologic classification, and allow greater confidence in results. This effort paves the way for a climate change analysis for the Pacific Northwest that is currently underway, as well as expansion into the southwest (California, Arizona, and Nevada). This dataset contains a high resolutio

  12. Combined Use of SAR and Optical Satellite Images for Landscape Diversity Assessment

    NASA Astrophysics Data System (ADS)

    Kuchma, Tetyana

    2016-08-01

    Land cover change analysis is essential for effective land use management and biodiversity conservation. The advantages of Sentinel-1 and Landsat-8 image fusion for land cover classification and landscape diversity maps development were studied. The methodology of landscape metrics interpretation for sustainable land use planning is developed and tested on agricultural landscapes in Ukraine.

  13. Multistage Adaptive Testing for a Large-Scale Classification Test: Design, Heuristic Assembly, and Comparison with Other Testing Modes. ACT Research Report Series, 2012 (6)

    ERIC Educational Resources Information Center

    Zheng, Yi; Nozawa, Yuki; Gao, Xiaohong; Chang, Hua-Hua

    2012-01-01

    Multistage adaptive tests (MSTs) have gained increasing popularity in recent years. MST is a balanced compromise between linear test forms (i.e., paper-and-pencil testing and computer-based testing) and traditional item-level computer-adaptive testing (CAT). It combines the advantages of both. On one hand, MST is adaptive (and therefore more…

  14. Binary Classification of an Unknown Object through Atmospheric Turbulence Using a Polarimetric Blind-Deconvolution Algorithm Augmented with Adaptive Degree of Linear Polarization Priors

    DTIC Science & Technology

    2012-03-01

    determine the stopping criterion for the material-classification algorithm. . . . . . . . . . . . . . 38 4.1. Photograph of the Stokes polarimeter used to...emerged as a powerful tool to enhance understanding of an underlying scene of inter- est. For example, using polarimetric imagery, Wolff presented a...geometry. The proposed method enhances the poor performance of the previously developed material-classification al- gorithm for near-normal collection

  15. Landscaping for energy efficiency

    SciTech Connect

    1995-04-01

    This publication by the National Renewable Energy Laboratory addresses the use of landscaping for energy efficiency. The topics of the publication include minimizing energy expenses; landscaping for a cleaner environment; climate, site, and design considerations; planning landscape; and selecting and planting trees and shrubs. A source list for more information on landscaping for energy efficiency and a reading list are included.

  16. Individual dispersal, landscape connectivity and ecological networks.

    PubMed

    Baguette, Michel; Blanchet, Simon; Legrand, Delphine; Stevens, Virginie M; Turlure, Camille

    2013-05-01

    Connectivity is classically considered an emergent property of landscapes encapsulating individuals' flows across space. However, its operational use requires a precise understanding of why and how organisms disperse. Such movements, and hence landscape connectivity, will obviously vary according to both organism properties and landscape features. We review whether landscape connectivity estimates could gain in both precision and generality by incorporating three fundamental outcomes of dispersal theory. Firstly, dispersal is a multi-causal process; its restriction to an 'escape reaction' to environmental unsuitability is an oversimplification, as dispersing individuals can leave excellent quality habitat patches or stay in poor-quality habitats according to the relative costs and benefits of dispersal and philopatry. Secondly, species, populations and individuals do not always react similarly to those cues that trigger dispersal, which sometimes results in contrasting dispersal strategies. Finally, dispersal is a major component of fitness and is thus under strong selective pressures, which could generate rapid adaptations of dispersal strategies. Such evolutionary responses will entail spatiotemporal variation in landscape connectivity. We thus strongly recommend the use of genetic tools to: (i) assess gene flow intensity and direction among populations in a given landscape; and (ii) accurately estimate landscape features impacting gene flow, and hence landscape connectivity. Such approaches will provide the basic data for planning corridors or stepping stones aiming at (re)connecting local populations of a given species in a given landscape. This strategy is clearly species- and landscape-specific. But we suggest that the ecological network in a given landscape could be designed by stacking up such linkages designed for several species living in different ecosystems. This procedure relies on the use of umbrella species that are representative of other species

  17. Improving land cover classification using input variables derived from a geographically weighted principal components analysis

    NASA Astrophysics Data System (ADS)

    Comber, Alexis J.; Harris, Paul; Tsutsumida, Narumasa

    2016-09-01

    This study demonstrates the use of a geographically weighted principal components analysis (GWPCA) of remote sensing imagery to improve land cover classification accuracy. A principal components analysis (PCA) is commonly applied in remote sensing but generates global, spatially-invariant results. GWPCA is a local adaptation of PCA that locally transforms the image data, and in doing so, can describe spatial change in the structure of the multi-band imagery, thus directly reflecting that many landscape processes are spatially heterogenic. In this research the GWPCA localised loadings of MODIS data are used as textural inputs, along with GWPCA localised ranked scores and the image bands themselves to three supervised classification algorithms. Using a reference data set for land cover to the west of Jakarta, Indonesia the classification procedure was assessed via training and validation data splits of 80/20, repeated 100 times. For each classification algorithm, the inclusion of the GWPCA loadings data was found to significantly improve classification accuracy. Further, but more moderate improvements in accuracy were found by additionally including GWPCA ranked scores as textural inputs, data that provide information on spatial anomalies in the imagery. The critical importance of considering both spatial structure and spatial anomalies of the imagery in the classification is discussed, together with the transferability of the new method to other studies. Research topics for method refinement are also suggested.

  18. Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher's Geometric Model?

    PubMed

    Blanquart, François; Bataillon, Thomas

    2016-06-01

    The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes.

  19. [Characteristic study on village landscape patterns in Sichuan Basin hilly region based on high resolution IKONOS remote sensing].

    PubMed

    Li, Shoucheng; Liu, Wenquan; Cheng, Xu; Ellis, Erle C

    2005-10-01

    To realize the landscape programming of agro-ecosystem management, landscape-stratification can provide us the best understanding of landscape ecosystem at very detailed scales. For this purpose, the village landscapes in densely populated Jintang and Jianyang Counties of Sichuan Basin hilly region were mapped from high resolution (1 m) IKONOS satellite imagery by using a standardized 4 level ecological landscape classification and mapping system in a regionally-representative sample of five 500 x 500 m2 landscape quadrats (sample plots). Based on these maps, the spatial patterns were analyzed by landscape indicators, which demonstrated a large variety of landscape types or ecotopes across the village landscape of this region, with diversity indexes ranging from 1.08 to 2.26 at different levels of the landscape classification system. The richness indices ranged from 42.2% to 58.6 %, except that for the landcover at 85 %. About 12.5 % of the ecotopes were distributed in the same way in each landscape sample, and the remaining 87.5% were distributed differently. The landscape fragmentation indices varied from 2.93 to 4.27 across sample plots, and from 2.86 to 5.63 across classification levels. The population density and the road and hamlet areas had strong linear correlations with some landscape indicators, and especially, the correlation coefficients of hamlet areas with fractal indexes and fragmental dimensions were 0.957* and 0.991**, respectively. The differences in most landscape pattern indices across sample plots and landscape classes were statistically significant, indicating that cross-scale mapping and classification of village landscapes could provide more detailed information on landscape patterns than those from a single level of classification.

  20. Multi-scale curvature for automated identification of glaciated mountain landscapes.

    PubMed

    Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R; Schrott, Lothar

    2014-03-15

    Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.

  1. [Land use and land cover charnge (LUCC) and landscape service: Evaluation, mapping and modeling].

    PubMed

    Song, Zhang-jian; Cao, Yu; Tan, Yong-zhong; Chen, Xiao-dong; Chen, Xian-peng

    2015-05-01

    Studies on ecosystem service from landscape scale aspect have received increasing attention from researchers all over the world. Compared with ecosystem scale, it should be more suitable to explore the influence of human activities on land use and land cover change (LUCC), and to interpret the mechanisms and processes of sustainable landscape dynamics on landscape scale. Based on comprehensive and systematic analysis of researches on landscape service, this paper firstly discussed basic concepts and classification of landscape service. Then, methods of evaluation, mapping and modeling of landscape service were analyzed and concluded. Finally, future trends for the research on landscape service were proposed. It was put forward that, exploring further connotation and classification system of landscape service, improving methods and quantitative indicators for evaluation, mapping and modelling of landscape service, carrying out long-term integrated researches on landscape pattern-process-service-scale relationships and enhancing the applications of theories and methods on landscape economics and landscape ecology are very important fields of the research on landscape service in future.

  2. Soil erosion dynamics response to landscape pattern.

    PubMed

    Ouyang, Wei; Skidmore, Andrew K; Hao, Fanghua; Wang, Tiejun

    2010-02-15

    Simulating soil erosion variation with a temporal land use database reveals long-term fluctuations in landscape patterns, as well as priority needs for soil erosion conservation. The application of a multi-year land use database in support of a Soil Water Assessment Tool (SWAT) led to an accurate assessment, from 1977 to 2006, of erosion in the upper watershed of the Yellow River. At same time, the impacts of land use and landscape service features on soil erosion load were assessed. A series of supervised land use classifications of Landsat images characterized variations in land use and landscape patterns over three decades. The SWAT database was constructed with soil properties, climate and elevation data. Using water flow and sand density data as parameters, regional soil erosion load was simulated. A numerical statistical model was used to relate soil erosion to land use and landscape. The results indicated that decadal decrease of grassland areas did not pose a significant threat to soil erosion, while the continual increase of bare land, water area and farmland increased soil erosion. Regional landscape variation also had a strong relationship with erosion. Patch level landscape analyses demonstrated that larger water area led to more soil erosion. The patch correlation indicated that contagious grassland patches reduced soil erosion yield. The increased grassland patches led to more patch edges, in turn increasing the sediment transportation from the patch edges. The findings increase understanding of the temporal variation in soil erosion processes, which is the basis for preventing local pollution.

  3. Landscape Management: Field Supervisor.

    ERIC Educational Resources Information Center

    Newton, Deborah; Newton, Steve

    This module is the third volume in a series of instructional materials on landscape management. The materials are designed to help teachers train students in the job skills they will need in landscape occupations. The module contains six instructional units that cover the following topics: orientation; basic landscape design principles; irrigation…

  4. Manifold alignment for classification of multitemporal hyperspectral image data

    NASA Astrophysics Data System (ADS)

    Yang, Hsiu-Han

    Analyzing remotely sensed images to obtain land cover classification maps is an effective approach for acquiring information over landscapes that can be accomplished over extended areas with limited ground surveys. Further, with advances in remote sensing technology, spaceborne hyperspectral sensors provide the capability to acquire a set of images that have both high spectral and temporal resolution. These images are suitable for monitoring and analyzing environmental changes with subtle spectral characteristics. However, inherent characteristics of multitemporal hyperspectral images, including high dimensionality, nonlinearity, and nonstationarity phenomena over time and across large areas, pose several challenges for classification. This research addresses the issues of classification tasks in the presence of spectral shifts within multitemporal hyperspectral images by leveraging the concept of the data manifold. Although manifold learning has been applied successfully in single image hyperspectral data classification to address high dimensionality and nonlinear spectral responses, research related to manifold learning for multitemporal classification studies is limited. The proposed approaches utilize spectral signatures and spatial proximity to construct similar "local" geometries of temporal images. By aligning these underlying manifolds optimally, the impacts of nonstationary effects are mitigated and classification is accomplished in a representative temporal data manifold. "Global" manifolds learned from temporal hyperspectral images have a major advantage in faithful representation of the data in an image, such as retaining relationships between different classes. Local manifolds are favored in discriminating difficult classes and for computation efficiency. A new hybrid global-local manifold alignment method that combines the advantages of global and local manifolds for effective multitemporal image classification is also proposed. Results illustrate the

  5. Landscape analysis: Theoretical considerations and practical needs

    USGS Publications Warehouse

    Godfrey, A.E.; Cleaves, E.T.

    1991-01-01

    Numerous systems of land classification have been proposed. Most have led directly to or have been driven by an author's philosophy of earth-forming processes. However, the practical need of classifying land for planning and management purposes requires that a system lead to predictions of the results of management activities. We propose a landscape classification system composed of 11 units, from realm (a continental mass) to feature (a splash impression). The classification concerns physical aspects rather than economic or social factors; and aims to merge land inventory with dynamic processes. Landscape units are organized using a hierarchical system so that information may be assembled and communicated at different levels of scale and abstraction. Our classification uses a geomorphic systems approach that emphasizes the geologic-geomorphic attributes of the units. Realm, major division, province, and section are formulated by subdividing large units into smaller ones. For the larger units we have followed Fenneman's delineations, which are well established in the North American literature. Areas and districts are aggregated into regions and regions into sections. Units smaller than areas have, in practice, been subdivided into zones and smaller units if required. We developed the theoretical framework embodied in this classification from practical applications aimed at land use planning and land management in Maryland (eastern Piedmont Province near Baltimore) and Utah (eastern Uinta Mountains). ?? 1991 Springer-Verlag New York Inc.

  6. Land cover classification in multispectral satellite imagery using sparse approximations on learned dictionaries

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a modified Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using CoSA: unsupervised Clustering of Sparse Approximations. We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska (USA). Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g., soil moisture and inundation), and topographic/geomorphic characteristics. In this paper, we explore learning from both raw multispectral imagery, as well as normalized band difference indexes. We explore a quantitative metric to evaluate the spectral properties of the clusters, in order to potentially aid in assigning land cover categories to the cluster labels.

  7. Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

    NASA Astrophysics Data System (ADS)

    Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

    2016-06-01

    This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

  8. Using remote sensing products to classify landscape. A multi-spatial resolution approach

    NASA Astrophysics Data System (ADS)

    García-Llamas, Paula; Calvo, Leonor; Álvarez-Martínez, José Manuel; Suárez-Seoane, Susana

    2016-08-01

    The European Landscape Convention encourages the inventory and characterization of landscapes for environmental management and planning actions. Among the range of data sources available for landscape classification, remote sensing has substantial applicability, although difficulties might arise when available data are not at the spatial resolution of operational interest. We evaluated the applicability of two remote sensing products informing on land cover (the categorical CORINE map at 30 m resolution and the continuous NDVI spectral index at 1 km resolution) in landscape classification across a range of spatial resolutions (30 m, 90 m, 180 m, 1 km), using the Cantabrian Mountains (NW Spain) as study case. Separate landscape classifications (using topography, urban influence and land cover as inputs) were accomplished, one per each land cover dataset and spatial resolution. Classification accuracy was estimated through confusion matrixes and uncertainty in terms of both membership probability and confusion indices. Regarding landscape classifications based on CORINE, both typology and number of landscape classes varied across spatial resolutions. Classification accuracy increased from 30 m (the original resolution of CORINE) to 90m, decreasing towards coarser resolutions. Uncertainty followed the opposite pattern. In the case of landscape classifications based on NDVI, the identified landscape patterns were geographically structured and showed little sensitivity to changes across spatial resolutions. Only the change from 1 km (the original resolution of NDVI) to 180 m improved classification accuracy. The value of confusion indices increased with resolution. We highlight the need for greater effort in selecting data sources at the suitable spatial resolution, matching regional peculiarities and minimizing error and uncertainty.

  9. Combining QuickBird, LiDAR, and GIS topography indices to identify a single native tree species in a complex landscape using an object-based classification approach

    NASA Astrophysics Data System (ADS)

    Pham, Lien T. H.; Brabyn, Lars; Ashraf, Salman

    2016-08-01

    There are now a wide range of techniques that can be combined for image analysis. These include the use of object-based classifications rather than pixel-based classifiers, the use of LiDAR to determine vegetation height and vertical structure, as well terrain variables such as topographic wetness index and slope that can be calculated using GIS. This research investigates the benefits of combining these techniques to identify individual tree species. A QuickBird image and low point density LiDAR data for a coastal region in New Zealand was used to examine the possibility of mapping Pohutukawa trees which are regarded as an iconic tree in New Zealand. The study area included a mix of buildings and vegetation types. After image and LiDAR preparation, single tree objects were identified using a range of techniques including: a threshold of above ground height to eliminate ground based objects; Normalised Difference Vegetation Index and elevation difference between the first and last return of LiDAR data to distinguish vegetation from buildings; geometric information to separate clusters of trees from single trees, and treetop identification and region growing techniques to separate tree clusters into single tree crowns. Important feature variables were identified using Random Forest, and the Support Vector Machine provided the classification. The combined techniques using LiDAR and spectral data produced an overall accuracy of 85.4% (Kappa 80.6%). Classification using just the spectral data produced an overall accuracy of 75.8% (Kappa 67.8%). The research findings demonstrate how the combining of LiDAR and spectral data improves classification for Pohutukawa trees.

  10. Landscape ecological security assessment based on projection pursuit in Pearl River Delta.

    PubMed

    Gao, Yang; Wu, Zhifeng; Lou, Quansheng; Huang, Huamei; Cheng, Jiong; Chen, Zhangli

    2012-04-01

    Regional landscape ecological security is an important issue for ecological security, and has a great influence on national security and social sustainable development. The Pearl River Delta (PRD) in southern China has experienced rapid economic development and intensive human activities in recent years. This study, based on landscape analysis, provides a method to discover the alteration of character among different landscape types and to understand the landscape ecological security status. Based on remotely sensed products of the Landsat 5 TM images in 1990 and the Landsat 7 ETM+ images in 2005, landscape classification maps of nine cities in the PRD were compiled by implementing Remote Sensing and Geographic Information System technology. Several indices, including aggregation, crush index, landscape shape index, Shannon's diversity index, landscape fragile index, and landscape security adjacent index, were applied to analyze spatial-temporal characteristics of landscape patterns in the PRD. A landscape ecological security index based on these outcomes was calculated by projection pursuit using genetic algorithm. The landscape ecological security of nine cities in the PRD was thus evaluated. The main results of this research are listed as follows: (1) from 1990 to 2005, the aggregation index, crush index, landscape shape index, and Shannon's diversity index of nine cities changed little in the PRD, while the landscape fragile index and landscape security adjacent index changed obviously. The landscape fragile index of nine cities showed a decreasing trend; however, the landscape security adjacent index has been increasing; (2) from 1990 to 2005, landscape ecology of the cities of Zhuhai and Huizhou maintained a good security situation. However, there was a relatively low value of ecological security in the cities of Dongguan and Foshan. Except for Foshan and Guangzhou, whose landscape ecological security situation were slightly improved, the cities had reduced

  11. Adaptive reshaping of objects in (multiparameter) Hilbert space for enhanced detection and classification: an application of receiver operating curve statistics to laser-based mass spectroscopy.

    PubMed

    Romanov, Dmitri A; Healy, Dennis M; Brady, John J; Levis, Robert J

    2008-05-01

    We propose a new approach to the classical detection problem of discrimination of a true signal of interest from an interferent signal, which may be applied to the area of chemical sensing. We show that the detection performance, as quantified by the receiver operating curve (ROC), can be substantially improved when the signal is represented by a multicomponent data set that is actively manipulated by means of a shaped laser probe pulse. In this case, the signal sought (agent) and the interfering signal (interferent) are visualized by vectors in a multidimensional detection space. Separation of these vectors can be achieved by adaptive modification of a probing laser pulse to actively manipulate the Hamiltonian of the agent and interferent. We demonstrate one implementation of the concept of adaptive rotation of signal vectors to chemical agent detection by means of strong-field time-of-flight mass spectrometry.

  12. Simulating natural selection in landscape genetics.

    PubMed

    Landguth, E L; Cushman, S A; Johnson, N A

    2012-03-01

    Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially-explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors--mutation, gene flow, genetic drift and selection--that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces). We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency. The program provides a valuable tool (cdpop v1.0; http://cel.dbs.umt.edu/software/CDPOP/) for the study of evolutionary landscape genetics that allows explicit evaluation of the interactions between gene flow and selection in complex landscapes.

  13. Spatial transferability of landscape-based hydrological models

    NASA Astrophysics Data System (ADS)

    Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert

    2015-04-01

    Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph

  14. Predictability of evolution in complex fitness landscapes

    NASA Astrophysics Data System (ADS)

    Krug, Joachim

    2013-03-01

    Evolutionary adaptations arise from an intricate interplay of deterministic selective forces and random reproductive or mutational events, and the relative roles of these two types of influences is the subject of a long-standing controversy. In general, the predictability of adaptive trajectories is governed by the genetic constraints imposed by the structure of the underlying fitness landscape as well as by the supply rate and effect size of beneficial mutations. On the level of single mutational steps, evolutionary predictability depends primarily on the distribution of fitness effects, with heavy-tailed distributions giving rise to highly predictable behavior. The genetic constraints imposed by the fitness landscape can be quantified through the statistical properties of accessible mutational pathways along which fitness increases monotonically. I will report on recent progress in the understanding of evolutionary accessibility in model landscapes and compare the predictions of the models to empirical data. Finally, I will describe extensive Wright-Fisher-type simulations of asexual adaptation on an empirical fitness landscape. By quantifying predictability through the entropies of the distributions of evolutionary trajectories and endpoints we show that, contrary to common wisdom, the predictability of evolution depends non-monotonically on population size. Supported by DFG within SFB 680 and SPP 1590.

  15. Vulnerability of Oregon Hydrologic Landscapes and Streamflow to Climate Change - 5/20/2014

    EPA Science Inventory

    Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors. Such assessments could be particularly useful in determining hydrologic vulnerability from climate change. A...

  16. Applicability of Hydrologic Landscapes for Model Calibration at the Watershed Scale in the Pacific Northwest

    EPA Science Inventory

    The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of tec...

  17. Another Paper Landscape?

    ERIC Educational Resources Information Center

    Radlak, Ted

    2001-01-01

    Describes the University of Toronto's extensive central campus revitalization plan to create lush landscapes that add to the school's image and attractiveness. Drawings and photographs are included. (GR)

  18. Landscape ecology of eastern coyotes based on large-scale estimates of abundance.

    PubMed

    Kays, Roland W; Gompper, Matthew E; Ray, Justina C

    2008-06-01

    Since their range expansion into eastern North America in the mid-1900s, coyotes (Canis latrans) have become the region's top predator. Although widespread across the region, coyote adaptation to eastern forests and use of the broader landscape are not well understood. We studied the distribution and abundance of coyotes by collecting coyote feces from 54 sites across a diversity of landscapes in and around the Adirondacks of northern New York. We then genotyped feces with microsatellites and found a close correlation between the number of detected individuals and the total number of scats at a site. We created habitat models predicting coyote abundance using multi-scale vegetation and landscape data and ranked them with an information-theoretic model selection approach. These models allow us to reject the hypothesis that eastern forests are unsuitable habitat for coyotes as their abundance was positively correlated with forest cover and negatively correlated with measures of rural non-forest landscapes. However, measures of vegetation structure turned out to be better predictors of coyote abundance than generalized "forest vs. open" classification. The best supported models included those measures indicative of disturbed forest, especially more open canopies found in logged forests, and included natural edge habitats along water courses. These forest types are more productive than mature forests and presumably host more prey for coyotes. A second model with only variables that could be mapped across the region highlighted the lower density of coyotes in areas with high human settlement, as well as positive relationships with variables such as snowfall and lakes that may relate to increased numbers and vulnerability of deer. The resulting map predicts coyote density to be highest along the southwestern edge of the Adirondack State Park, including Tug Hill, and lowest in the mature forests and more rural areas of the central and eastern Adirondacks. Together, these

  19. The adaptive computer-aided diagnosis system based on tumor sizes for the classification of breast tumors detected at screening ultrasound.

    PubMed

    Moon, Woo Kyung; Chen, I-Ling; Chang, Jung Min; Shin, Sung Ui; Lo, Chung-Ming; Chang, Ruey-Feng

    2017-04-01

    Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1cm or smaller. An adaptive computer-aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (<1cm and ⩾1cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8% (63/77), 85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US.

  20. Vocal development in a Waddington landscape

    PubMed Central

    Teramoto, Yayoi; Takahashi, Daniel Y; Holmes, Philip; Ghazanfar, Asif A

    2017-01-01

    Vocal development is the adaptive coordination of the vocal apparatus, muscles, the nervous system, and social interaction. Here, we use a quantitative framework based on optimal control theory and Waddington’s landscape metaphor to provide an integrated view of this process. With a biomechanical model of the marmoset monkey vocal apparatus and behavioral developmental data, we show that only the combination of the developing vocal tract, vocal apparatus muscles and nervous system can fully account for the patterns of vocal development. Together, these elements influence the shape of the monkeys’ vocal developmental landscape, tilting, rotating or shifting it in different ways. We can thus use this framework to make quantitative predictions regarding how interfering factors or experimental perturbations can change the landscape within a species, or to explain comparative differences in vocal development across species DOI: http://dx.doi.org/10.7554/eLife.20782.001 PMID:28092262

  1. Exploring the fitness landscape of poliovirus

    NASA Astrophysics Data System (ADS)

    Bianco, Simone; Acevedo, Ashely; Andino, Raul; Tang, Chao

    2012-02-01

    RNA viruses are known to display extraordinary adaptation capabilities to different environments, due to high mutation rates. Their very dynamical evolution is captured by the quasispecies concept, according to which the viral population forms a swarm of genetic variants linked through mutation, which cooperatively interact at a functional level and collectively contribute to the characteristics of the population. The description of the viral fitness landscape becomes paramount towards a more thorough understanding of the virus evolution and spread. The high mutation rate, together with the cooperative nature of the quasispecies, makes it particularly challenging to explore its fitness landscape. I will present an investigation of the dynamical properties of poliovirus fitness landscape, through both the adoption of new experimental techniques and theoretical models.

  2. Properties of selected mutations and genotypic landscapes under Fisher’s Geometric Model

    PubMed Central

    Blanquart, François; Achaz, Guillaume; Bataillon, Thomas; Tenaillon, Olivier

    2014-01-01

    The fitness landscape – the mapping between genotypes and fitness – determines properties of the process of adaptation. Several small genotypic fitness landscapes have recently been built by selecting a handful of beneficial mutations and measuring fitness of all combinations of these mutations. Here we generate several testable predictions for the properties of these small genotypic landscapes under Fisher’s geometric model of adaptation. When the ancestral strain is far from the fitness optimum, we analytically compute the fitness effect of selected mutations and their epistatic interactions. Epistasis may be negative or positive on average depending on the distance of the ancestral genotype to the optimum and whether mutations were independently selected, or co-selected in an adaptive walk. Simulations show that genotypic landscapes built from Fisher’s model are very close to an additive landscape when the ancestral strain is far from the optimum. However, when it is close to the optimum, a large diversity of landscape with substantial roughness and sign epistasis emerged. Strikingly, small genotypic landscapes built from several replicate adaptive walks on the same underlying landscape were highly variable, suggesting that several realizations of small genotypic landscapes are needed to gain information about the underlying architecture of the fitness landscape. PMID:25311558

  3. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    DOE PAGES

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

    2014-12-09

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

  4. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    SciTech Connect

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-12-09

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.

  5. A checklist for ecological management of landscapes for conservation.

    PubMed

    Lindenmayer, David; Hobbs, Richard J; Montague-Drake, Rebecca; Alexandra, Jason; Bennett, Andrew; Burgman, Mark; Cale, Peter; Calhoun, Aram; Cramer, Viki; Cullen, Peter; Driscoll, Don; Fahrig, Lenore; Fischer, Joern; Franklin, Jerry; Haila, Yrjo; Hunter, Malcolm; Gibbons, Philip; Lake, Sam; Luck, Gary; MacGregor, Chris; McIntyre, Sue; Nally, Ralph Mac; Manning, Adrian; Miller, James; Mooney, Hal; Noss, Reed; Possingham, Hugh; Saunders, Denis; Schmiegelow, Fiona; Scott, Michael; Simberloff, Dan; Sisk, Tom; Tabor, Gary; Walker, Brian; Wiens, John; Woinarski, John; Zavaleta, Erika

    2008-01-01

    The management of landscapes for biological conservation and ecologically sustainable natural resource use are crucial global issues. Research for over two decades has resulted in a large literature, yet there is little consensus on the applicability or even the existence of general principles or broad considerations that could guide landscape conservation. We assess six major themes in the ecology and conservation of landscapes. We identify 13 important issues that need to be considered in developing approaches to landscape conservation. They include recognizing the importance of landscape mosaics (including the integration of terrestrial and aquatic areas), recognizing interactions between vegetation cover and vegetation configuration, using an appropriate landscape conceptual model, maintaining the capacity to recover from disturbance and managing landscapes in an adaptive framework. These considerations are influenced by landscape context, species assemblages and management goals and do not translate directly into on-the-ground management guidelines but they should be recognized by researchers and resource managers when developing guidelines for specific cases. Two crucial overarching issues are: (i) a clearly articulated vision for landscape conservation and (ii) quantifiable objectives that offer unambiguous signposts for measuring progress.

  6. How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

    PubMed

    du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian

    2016-09-01

    Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.

  7. BATS AND BT INSECT RESISTANCE ON AGRICULTURAL LANDSCAPES

    EPA Science Inventory

    A landscape model that utilizes land cover classification data, insect life history, insect movement, and bat foraging pressure is developed that addresses the implementation of genetically modified crops in the Winter Garden region of Texas. The principal strategy for delaying r...

  8. Planetary Landscape Geography

    NASA Astrophysics Data System (ADS)

    Hargitai, H.

    INTRODUCTION Landscape is one of the most often used category in physical ge- ography. The term "landshap" was introduced by Dutch painters in the 15-16th cen- tury. [1] The elements that build up a landscape (or environment) on Earth consists of natural (biogenic and abiogenic - lithologic, atmospheric, hydrologic) and artificial (antropogenic) factors. Landscape is a complex system of these different elements. The same lithology makes different landscapes under different climatic conditions. If the same conditions are present, the same landscape type will appear. Landscapes build up a hierarchic system and cover the whole surface. On Earth, landscapes can be classified and qualified according to their characteristics: relief forms (morphology), and its potential economic value. Aesthetic and subjective parameters can also be considered. Using the data from landers and data from orbiters we can now classify planetary landscapes (these can be used as geologic mapping units as well). By looking at a unknown landscape, we can determine the processes that created it and its development history. This was the case in the Pathfinder/Sojourner panoramas. [2]. DISCUSSION Planetary landscape evolution. We can draw a raw landscape develop- ment history by adding the different landscape building elements to each other. This has a strong connection with the planet's thermal evolution (age of the planet or the present surface materials) and with orbital parameters (distance from the central star, orbit excentricity etc). This way we can build a complex system in which we use differ- ent evolutional stages of lithologic, atmospheric, hydrologic and biogenic conditions which determine the given - Solar System or exoplanetary - landscape. Landscape elements. "Simple" landscapes can be found on asteroids: no linear horizon is present (not differentiated body, only impact structures), no atmosphere (therefore no atmospheric scattering - black sky as part of the landscape) and no

  9. Union of phylogeography and landscape genetics

    PubMed Central

    Rissler, Leslie J.

    2016-01-01

    Phylogeography and landscape genetics have arisen within the past 30 y. Phylogeography is said to be the bridge between population genetics and systematics, and landscape genetics the bridge between landscape ecology and population genetics. Both fields can be considered as simply the amalgamation of classic biogeography with genetics and genomics; however, they differ in the temporal, spatial, and organismal scales addressed and the methodology used. I begin by briefly summarizing the history and purview of each field and suggest that, even though landscape genetics is a younger field (coined in 2003) than phylogeography (coined in 1987), early studies by Dobzhansky on the “microgeographic races” of Linanthus parryae in the Mojave Desert of California and Drosophila pseudoobscura across the western United States presaged the fields by over 40 y. Recent advances in theory, models, and methods have allowed researchers to better synthesize ecological and evolutionary processes in their quest to answer some of the most basic questions in biology. I highlight a few of these novel studies and emphasize three major areas ripe for investigation using spatially explicit genomic-scale data: the biogeography of speciation, lineage divergence and species delimitation, and understanding adaptation through time and space. Examples of areas in need of study are highlighted, and I end by advocating a union of phylogeography and landscape genetics under the more general field: biogeography. PMID:27432989

  10. Applicability of Hydrologic Landscapes for Model Calibration ...

    EPA Pesticide Factsheets

    The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of techniques were applied to the HL assessment unit composition in watersheds across the Pacific Northwest to aggregate the hydrologic behavior of the Hydrologic Landscapes from the assessment unit scale to the watershed scale. This non-trivial solution both emphasizes HL classifications within the watershed that provide that majority of moisture surplus/deficit and considers the relative position (upstream vs. downstream) of these HL classifications. A clustering algorithm was applied to the HL-based characterization of assessment units within 185 watersheds to help organize watersheds into nine classes hypothesized to have similar hydrologic behavior. The HL-based classes were used to organize and describe hydrologic behavior information about watershed classes and both predictions and validations were independently performed with regard to the general magnitude of six hydroclimatic signature values. A second cluster analysis was then performed using the independently calculated signature values as similarity metrics, and it was found that the six signature clusters showed substantial overlap in watershed class membership to those in the HL-based classes. One hypothesis set forward from thi

  11. Computerized Classification Testing with the Rasch Model

    ERIC Educational Resources Information Center

    Eggen, Theo J. H. M.

    2011-01-01

    If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

  12. Land use classification in Bolivia

    NASA Technical Reports Server (NTRS)

    Brockmann, C. E.; Brooner, W. G.

    1975-01-01

    The Bolivian LANDSAT Program is an integrated, multidisciplinary project designed to provide thematic analysis of LANDSAT, Skylab, and other remotely sensed data for natural resource management and development in Bolivia, is discussed. Among the first requirements in the program is the development of a legend, and appropriate methodologies, for the analysis and classification of present land use based on landscape cover. The land use legend for Bolivia consists of approximately 80 categories in a hierarchical organization which may be collapsed for generalization, or expanded for greater detail. The categories, and their definitions, provide for both a graphic and textual description of the complex and diverse landscapes found in Bolivia, and are designed for analysis from LANDSAT and other remotely sensed data at scales of 1:1,000,000 and 1:250,000. Procedures and example products developed are described and illustrated, for the systematic analysis and mapping of present land use for all of Bolivia.

  13. AEDS Property Classification Code Manual.

    ERIC Educational Resources Information Center

    Association for Educational Data Systems, Washington, DC.

    The control and inventory of property items using data processing machines requires a form of numerical description or code which will allow a maximum of description in a minimum of space on the data card. An adaptation of a standard industrial classification system is given to cover any expendable warehouse item or non-expendable piece of…

  14. Elaboration of the third-generation world map of terrestrial landscapes as a model of the landscape sphere of the Earth

    NASA Astrophysics Data System (ADS)

    Romanova, Emma; Alexeeva, Nina; Arshinova, Marina; Klimanova, Oksana; Kovaleva, Tatiana; Kondratieva, Tatiana; Alyautdinov, Ali

    2016-04-01

    The first fundamental investigation aimed at the elaboration of the global map of terrestrial landscapes has resulted in a series of maps for the Physical-Geographical Atlas of the World (1964). Typological classification of landscapes and the concept of the zonal differentiation of terrestrial landscapes of the Earth became a basis for the maps of physical-geographical regions of individual continents and the global map of landscape types at the scale of 1:80 Mln. The next stage of research in the sphere of small-scale landscape regionalization and mapping of both natural and natural-anthropogenic landscapes has produced the global maps of Geographical Belts and Zonal Types of Terrestrial Landscapes (1988) and Present-Day Landscapes of the World (1992) at the scale of 1:15 Mln. By the end of the 1990-s similar maps of individual continents were compiled for the Nature and Resources of the Earth digital atlas. Recent decades saw further development of the idea of zone - sector - belt structure of the Earth's landscape sphere which includes several hierarchically subordinated natural-territorial levels. New theoretical studies and emergence of extensive information materials allowed starting the elaboration of a new (third-generation) map at the scales of 1:15 Mln to 1:5 Mln. A new classification of landscape units was suggested basing on the analysis of principal landscape-forming factors (climatic, lithogene and biogenic). A new cartographical model was developed specifying the following hierarchical levels: geographical belts, sectors, natural zones and sub-zones, classes and subclasses of landscapes. Classification criteria used for landscape systematization and mapping include both natural parameters (radiation balance, heat and moisture supply, structure of the vegetative period, biological productivity of vegetation, etc.) and anthropogenic indicators, thus providing for the evaluation of the geoecological state of landscapes (ecosystems of regional dimension

  15. Appendix E: Research papers. Use of remote sensing in landscape stratification for environmental impact assessment

    NASA Technical Reports Server (NTRS)

    Stanturf, J. A.; Heimbuch, D. G.

    1980-01-01

    A refinement to the matrix approach to environmental impact assessment is to use landscape units in place of separate environmental elements in the analysis. Landscape units can be delineated by integrating remotely sensed data and available single-factor data. A remote sensing approach to landscape stratification is described and the conditions under which it is superior to other approaches that require single-factor maps are indicated. Flowcharts show the steps necessary to develop classification criteria, delineate units and a map legend, and use the landscape units in impact assessment. Application of the approach to assessing impacts of a transmission line in Montana is presented to illustrate the method.

  16. Enhancement Through Landscaping.

    ERIC Educational Resources Information Center

    Lindley, Charles

    1985-01-01

    Landscaping can make the school environment more attractive, thus encouraging students' intellectual, emotional, and physical development. Guidelines are offered for comprehensive site planning, tree and plant selection, and grounds maintenance. (MLF)

  17. Effect of host species on the topography of fitness landscape for a plant RNA virus.

    PubMed

    Cervera, Héctor; Lalić, Jasna; Elena, Santiago F

    2016-08-31

    Adaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotype of individuals with their fitness. At the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the number of accessible mutational pathways and of possible fitness peaks (i.e, adaptive solutions). For long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterize the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environments. In a previous study, we had characterized the properties of the empirical fitness landscape defined by the first five mutations fixed during adaptation of tobacco etch potyvirus (TEV) to a new experimental host, Arabidopsis thaliana Here we evaluate the topography of this landscape in the ancestral host Nicotiana tabacum Comparing the topographies of the landscape in the two hosts, we found that some features remain similar, such as the existence of fitness holes and the prevalence of epistasis, including cases of sign and of reciprocal sign that create rugged, uncorrelated and highly random topographies. However, we also observed significant differences in the fine-grained details among both landscapes due to changes in the fitness and epistatic interactions of some genotypes. Our results support the idea that not only fitness tradeoffs between hosts but also topographical incongruences among fitness landscapes in alternative hosts may contribute to virus specialization.

  18. Landscape evolution (A Review)

    PubMed Central

    Sharp, Robert P.

    1982-01-01

    Landscapes are created by exogenic and endogenic processes acting along the interface between the lithosphere and the atmosphere and hydrosphere. Various landforms result from the attack of weathering and erosion upon the highly heterogeneous lithospheric surface. Landscapes are dynamic, acutely sensitive to natural and artificial perturbation. Undisturbed, they can evolve through a succession of stages to a plain of low relief. Often, the progression of an erosion cycle is interrupted by tectonic or environmental changes; thus, many landscapes preserve vestiges of earlier cycles useful in reconstructing the recent history of Earth's surface. Landforms are bounded by slopes, so their evolution is best understood through study of slopes and the complex of factors controlling slope character and development. The substrate, biosphere, climatic environment, and erosive processes are principal factors. Creep of the disintegrated substrate and surface wash by water are preeminent. Some slopes attain a quasisteady form and recede parallel to themselves (backwearing); others become ever gentler with time (downwearing). The lovely convex/rectilinear/concave profile of many debris-mantled slopes reflects an interplay between creep and surface wash. Landscapes of greatest scenic attraction are usually those in which one or two genetic factors have strongly dominated or those perturbed by special events. Nature has been perturbing landscapes for billions of years, so mankind can learn about landscape perturbation from natural examples. Images

  19. Classification Analysis.

    ERIC Educational Resources Information Center

    Ball, Geoffrey H.

    Sorting things into groups is a basic intellectual task that allows people to simplify with minimal reduction in information. Classification techniques, which include both clustering and discrimination, provide step-by-step computer-based procedures for sorting things based on notions of generalized similarity and on the "class description"…

  20. The Adaptive Kernel Neural Network

    DTIC Science & Technology

    1989-10-01

    A neural network architecture for clustering and classification is described. The Adaptive Kernel Neural Network (AKNN) is a density estimation...classification layer. The AKNN retains the inherent parallelism common in neural network models. Its relationship to the kernel estimator allows the network to

  1. Quantifying landscape resilience using vegetation indices

    NASA Astrophysics Data System (ADS)

    Eddy, I. M. S.; Gergel, S. E.

    2014-12-01

    Landscape resilience refers to the ability of systems to adapt to and recover from disturbance. In pastoral landscapes, degradation can be measured in terms of increased desertification and/or shrub encroachment. In many countries across Central Asia, the use and resilience of pastoral systems has changed markedly over the past 25 years, influenced by centralized Soviet governance, private property rights and recently, communal resource governance. In Kyrgyzstan, recent governance reforms were in response to the increasing degradation of pastures attributed to livestock overgrazing. Our goal is to examine and map the landscape-level factors that influence overgrazing throughout successive governance periods. Here, we map and examine some of the spatial factors influencing landscape resilience in agro-pastoral systems in the Kyrgyzstan Republic where pastures occupy >50% of the country's area. We ask three questions: 1) which mechanisms of pasture degradation (desertification vs. shrub encroachment), are detectable using remote sensing vegetation indices?; 2) Are these degraded pastures associated with landscape features that influence herder mobility and accessibility (e.g., terrain, distance to other pastures)?; and 3) Have these patterns changed through successive governance periods? Using a chronosequence of Landsat imagery (1999-2014), NDVI and other VIs were used to identify trends in pasture condition during the growing season. Least-cost path distances as well as graph theoretic indices were derived from topographic factors to assess landscape connectivity (from villages to pastures and among pastures). Fieldwork was used to assess the feasibility and accuracy of this approach using the most recent imagery. Previous research concluded that low herder mobility hindered pasture use, thus we expect the distance from pasture to village to be an important predictor of pasture condition. This research will quantify the magnitude of pastoral degradation and test

  2. Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher’s Geometric Model?

    PubMed Central

    Blanquart, François; Bataillon, Thomas

    2016-01-01

    The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes. PMID:27052568

  3. Geomorpho-Landscapes

    NASA Astrophysics Data System (ADS)

    Farabollini, Piero; Lugeri, Francesca; Amadio, Vittorio

    2014-05-01

    Landscape is the object of human perceptions, being the image of spatial organization of elements and structures: mankind lives the first approach with the environment, viewing and feeling the landscape. Many definitions of landscape have been given over time: in this case we refer to the Landscape defined as the result of interaction among physical, biotic and anthropic phenomena acting in a different spatial-temporal scale (Foreman & Godron) Following an Aristotelic approach in studying nature, we can assert that " Shape is synthesis": so it is possible to read the land features as the expression of the endogenous and exogenous processes that mould earth surfaces; moreover, Landscape is the result of the interaction of natural and cultural components, and conditions the spatial-temporal development of a region. The study of the Landscape offers results useful in order to promote sustainable development, ecotourism, enhancement of natural and cultural heritage, popularization of the scientific knowledge. In Italy, a very important GIS-based tool to represent the territory is the "Carta della Natura" ("Map of Nature", presently coordinated by the ISPRA) that aims at assessing the state of the whole Italian territory, analyzing Landscape. The methodology follows a holistic approach, taking into consideration all the components of a landscape and then integrating the information. Each individual landscape, studied at different scales, shows distinctive elements: structural, which depend on physical form and specific spatial organization; functional, which depend on relationships created between biotic and abiotic elements, and dynamic, which depend on the successive evolution of the structure. The identification of the landscape units, recognized at different scales of analysis, allows an evaluation of the state of the land, referring to the dual risk/resource which characterizes the Italian country. An interesting opportunity is to discover those areas of unusual

  4. Differential responses of cryptic bat species to the urban landscape.

    PubMed

    Lintott, Paul R; Barlow, Kate; Bunnefeld, Nils; Briggs, Philip; Gajas Roig, Clara; Park, Kirsty J

    2016-04-01

    Urbanization is a key global driver in the modification of land use and has been linked to population declines even in widespread and relatively common species. Cities comprise a complex assortment of habitat types yet we know relatively little about the effects of their composition and spatial configuration on species distribution. Although many bat species exploit human resources, the majority of species are negatively impacted by urbanization. Here, we use data from the National Bat Monitoring Programme, a long-running citizen science scheme, to assess how two cryptic European bat species respond to the urban landscape. A total of 124 × 1 km(2) sites throughout Britain were surveyed. The landscape surrounding each site was mapped and classified into discrete biotope types (e.g., woodland). Generalized linear models were used to assess differences in the response to the urban environment between the two species, and which landscape factors were associated with the distributions of P. pipistrellus and P. pygmaeus. The relative prevalence of P. pygmaeus compared to P. pipistrellus was greater in urban landscapes with a higher density of rivers and lakes, whereas P. pipistrellus was frequently detected in landscapes comprising a high proportion of green space (e.g., parklands). Although P. pipistrellus is thought to be well adapted to the urban landscape, we found a strong negative response to urbanization at a relatively local scale (1 km), whilst P. pygmaeus was detected more regularly in wooded urban landscapes containing freshwater. These results show differential habitat use at a landscape scale of two morphologically similar species, indicating that cryptic species may respond differently to anthropogenic disturbance. Even species considered relatively common and well adapted to the urban landscape may respond negatively to the built environment highlighting the future challenges involved in maintaining biodiversity within an increasingly urbanized

  5. Termination Criteria for Computerized Classification Testing

    ERIC Educational Resources Information Center

    Thompson, Nathan A.

    2011-01-01

    Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…

  6. Seismic event classification system

    DOEpatents

    Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

    1994-01-01

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

  7. Seismic event classification system

    DOEpatents

    Dowla, F.U.; Jarpe, S.P.; Maurer, W.

    1994-12-13

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

  8. Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

    PubMed

    Cheng, Zhan-Hong; Zhang, Jin-Tun

    2005-09-01

    The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

  9. Landscapes, tourism, and conservation

    PubMed

    Burger

    2000-04-17

    One key aspect of global change is a decrease in ecological integrity as more and more landscapes are developed, leaving a mosaic of intact refuges and degraded patches that may not be sufficient for conserving biodiversity. While increases in human population and shifts in the distribution of people affect land use, the temporary movement of people can have major implications for conservation and biodiversity. Three examples are presented where recreation/tourism can enhance the conservation of land on a landscape scale, leading to habitat protection and biodiversity preservation: (1) Shorebirds often require a matrix of different habitat types during migratory stopovers, and ecotourism can serve as a catalyst for landscape scale protection of habitat. (2) Riparian habitats can serve as corridors to link diverse habitat patches, as well as serving as biodiversity hotspots. (3) Remediation and rehabilitation of contaminated lands, such as those of the US Department of Energy, aimed at developing recreational activities on the uncontaminated portions, can be the most economical form of re-development with no increase in human or ecological risk. Since large areas on many DOE sites have been undisturbed since the Second World War, when they were acquired, they contain unique or valuable ecosystems that serve an important role within their regional landscapes. In all three cases the judicious development of recreational/tourist interests can encourage both the conservation of habitats and the wise management of habitats on a landscape scale. While some species or habitats are too fragile for sustained tourism, many can be managed so that species, ecosystems and ecotourists flourish. By contributing to the economic base of regions, ecotourists/recreationists can influence the protection of land and biodiversity on a landscape scale, contributing to ecosystem management. The human dimensions of land preservation and biodiversity protection are key to long

  10. Development of a reproducible method for determining quantity of water and its configuration in a marsh landscape

    USGS Publications Warehouse

    Suir, Glenn M.; Evers, D. Elaine; Steyer, Gregory D.; Sasser, Charles E.

    2013-01-01

    Coastal Louisiana is a dynamic and ever-changing landscape. From 1956 to 2010, over 3,734 km2 of Louisiana's coastal wetlands have been lost due to a combination of natural and human-induced activities. The resulting landscape constitutes a mosaic of conditions from highly deteriorated to relatively stable with intact landmasses. Understanding how and why coastal landscapes change over time is critical to restoration and rehabilitation efforts. Historically, changes in marsh pattern (i.e., size and spatial distribution of marsh landmasses and water bodies) have been distinguished using visual identification by individual researchers. Difficulties associated with this approach include subjective interpretation, uncertain reproducibility, and laborious techniques. In order to minimize these limitations, this study aims to expand existing tools and techniques via a computer-based method, which uses geospatial technologies for determining shifts in landscape patterns. Our method is based on a raster framework and uses landscape statistics to develop conditions and thresholds for a marsh classification scheme. The classification scheme incorporates land and water classified imagery and a two-part classification system: (1) ratio of water to land, and (2) configuration and connectivity of water within wetland landscapes to evaluate changes in marsh patterns. This analysis system can also be used to trace trajectories in landscape patterns through space and time. Overall, our method provides a more automated means of quantifying landscape patterns and may serve as a reliable landscape evaluation tool for future investigations of wetland ecosystem processes in the northern Gulf of Mexico.

  11. Labyrinthine granular landscapes.

    PubMed

    Caps, H; Vandewalle, N

    2001-11-01

    We have numerically studied a model of granular landscape eroded by wind. We show the appearance of labyrinthic patterns when the wind orientation turns by 90 degrees. The occurrence of such structures is discussed. Moreover, we introduce the density n(k) of "defects" as the dynamic parameter governing the landscape evolution. A power-law behavior of n(k) is found as a function of time. In the case of wind variations, the exponent (drastically) shifts from two to one. The presence of two asymptotic values of n(k) implies the irreversibility of the labyrinthic formation process.

  12. Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning.

    PubMed

    Theobald, David M; Harrison-Atlas, Dylan; Monahan, William B; Albano, Christine M

    2015-01-01

    Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings.

  13. Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning

    PubMed Central

    Theobald, David M.; Harrison-Atlas, Dylan; Monahan, William B.; Albano, Christine M.

    2015-01-01

    Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings. PMID:26641818

  14. Multiple ecosystem services in a working landscape

    PubMed Central

    Eastburn, Danny J.; O’Geen, Anthony T.; Tate, Kenneth W.; Roche, Leslie M.

    2017-01-01

    Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services—specifically agricultural production, biodiversity and habitat, and soil health—across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments. PMID:28301475

  15. Restoring hydrologic function in urban landscapes with suburban subsoiling

    NASA Astrophysics Data System (ADS)

    Schwartz, Stuart S.; Smith, Brennan

    2016-12-01

    Dramatic persistent hydrologic changes accompany urban land development, most commonly attributed to increased impervious area and drainage infrastructure. Modern land development and mass grading practices also result in the routine development of urban landscapes with highly disturbed compacted soil profiles. The common predictable result is an urban pervious landscape with greatly diminished infiltration capacity in greenspace that might best be described as grass growing in a thin veneer of topsoil on compacted fill. This paper describes the use of soil decompaction and amendment to restore hydrologic function following the removal of an impervious asphalt playground at a public school in Baltimore, MD, USA. The combination of soil decompaction with deep ripping and compost amendment is referred to as suburban subsoiling, alluding to the adaptation of agricultural subsoiling practices to restore hydrologic function in disturbed compacted urban soils. In this field-scale comparison with standard grading and landscaping practices, suburban subsoiling supported the highest infiltration rates, with the densest turf cover, highest soil organic matter and root zone soil moisture, and the lowest soil bulk density. As a sustainable alternative to traditional grading and topsoiling practices, suburban subsoiling offers a proverbial win-win solution, providing superior landscaping and restored hydrologic services with lower life-cycle costs. Though significantly different than current grading and landscaping practices, suburban subsoiling can be readily integrated in modern land development with only minor incremental changes in standard practices. Suburban subsoiling can transform the built environment through superior sustainable landscaping that restores the hydrologic function of urban pervious landscapes.

  16. Biophysical Fitness Landscapes and Evolutionary Dynamics of Proteins

    NASA Astrophysics Data System (ADS)

    Manhart, Michael; Morozov, Alexandre

    2014-03-01

    The molecular biophysics of proteins fundamentally shapes their fitness landscapes and evolutionary dynamics. For example, the evolution of new function in a protein is constrained by the need to maintain folding stability. We investigate the role of molecular biophysics in protein evolution by developing a class of fitness landscapes based on protein folding and binding energetics. We characterize the properties of these landscapes, such as their epistasis, accessibility, and number of local maxima. We also use a recently-developed path-based approach to random walks on networks to analyze the dynamics of populations evolving on these landscapes, focusing especially on the distribution and diversity of adaptive trajectories. These models make qualitative predictions relevant to both natural evolution as well as directed evolution experiments.

  17. Shaping the Landscape.

    ERIC Educational Resources Information Center

    Naturescope, 1987

    1987-01-01

    Provides background information on various agents that change the landscape. Includes teaching activities on weathering, water, wind and ice erosion, plate tectonics, sedimentation, deposition, mountain building, and determining contour lines. Contains reproducible handouts and worksheets for two of the activities. (TW)

  18. The New Postsecondary Landscape

    ERIC Educational Resources Information Center

    Sandeen, Cathy

    2013-01-01

    In this essay, Cathy Sandeen states that the new postsecondary landscape requires looking at higher education as a system that provides multiple pathways in and through the various parts of the system, all with the goal of helping students complete a postsecondary degree, credential, or certificate. Sandeen observes two strengths in professional…

  19. Landscape Management: Field Operator.

    ERIC Educational Resources Information Center

    Smith, Carole A.

    These materials for a six-unit course were developed to prepare secondary and postsecondary students for entry-level positions in landscape management. The six units are on orientation, hand tools, light power equipment, water and watering techniques, planting and maintaining plant beds, and establishing and maintaining turf. The first section is…

  20. Landscape Management: Field Specialist.

    ERIC Educational Resources Information Center

    Newton, Deborah; Newton, Steve

    This module is the second volume in a series of three publications on landscape management. The module contains five instructional units that cover the following topics: orientation; equipment; irrigation systems and maintenance; plant material identification and pests; and turf identification and pests. Each instructional unit follows a standard…

  1. Landscape Designs for Schools.

    ERIC Educational Resources Information Center

    Taylor, Patricia

    This annotated bibliography includes summaries of 15 books and articles dealing with the topic of school landscape design, as well as a brief introduction that comments on recent trends in the field. Most of the publications cited are fairly recent; about two-thirds of them were published after 1970. Annotations range from approximately 125 to 250…

  2. A Curious Landscape

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This 'postcard' from the panoramic camera on the Mars Exploration Rover Opportunity shows the view of the martian landscape southwest of the rover. The image was taken in the late martian afternoon at Meridiani Planum on Mars, where Opportunity landed at approximately 9:05 p.m. PST on Saturday, Jan. 24.

  3. Landscapes of Learning.

    ERIC Educational Resources Information Center

    Greene, Maxine

    The commitment of educators to human development goals is a major theme of the booklet's 17 essays. Compiled from lectures written by the author during 1974-77, the essays explore individual potential, the cultural significance of various life situations, and personal fulfillment within each individual's particular landscape of work, experience,…

  4. Desert landscape irrigation

    SciTech Connect

    Quinones, R.

    1995-06-01

    Industrialization can take place in an arid environment if a long term, overall water management program is developed. The general rule to follow is that recharge must equal or exceed use. The main problem encountered in landscape projects is that everyone wants a lush jungle setting, tall shade trees, ferns, with a variety of floral arrangements mixed in. What we want, what we can afford, and what we get are not always the same. Vegetation that requires large quantities of water are not native to any desert. Surprisingly; there are various types of fruit trees, and vegetables that will thrive in the desert. Peaches, plums, nut trees, do well with drip irrigation as well as tomatoes. Shaded berry plans will also do well, the strawberry being one. In summary; if we match our landscape to our area, we can then design our irrigation system to maintain our landscape and grow a variety of vegetation in any arid or semiarid environment. The application of science and economics to landscaping has now come of age.

  5. LANDSCAPE MANAGEMENT PRACTICES

    EPA Science Inventory

    USDA Conservation Practices are applied at various scales ranging from a portion of a field or a specific farm operation to the watershed or landscape scale. The Conservation Effects Assessment Project is a joint effort of USDA Conservation and Research agencies to determine the...

  6. Landscape in Literature.

    ERIC Educational Resources Information Center

    Salter, Christopher L.; Lloyd, William J.

    One of a series of Resource Papers for College Geography, this thematic study guide focuses on literary setting and the personal space of fictional characters as an approach to comparative literary study, and concurrently uses fictional treatments of landscape and place as a means to encourage greater sensitivity to geographical and architectural…

  7. Landscapes. Artists' Workshop Series.

    ERIC Educational Resources Information Center

    King, Penny; Roundhill, Clare

    This instructional resource, designed to be used by and with elementary level students, provides inspiration for landscape painting by presenting the work of six different artists. These include: "Fuji in Clear Weather" (Katsushika Hokusai, 1823-29); "The Tree of Life" (Gustav Klimt, c. 1905-1909); "The Waterlily…

  8. Sharing a Disparate Landscape

    ERIC Educational Resources Information Center

    Ali-Khan, Carolyne

    2010-01-01

    Working across boundaries of power, identity, and political geography is fraught with difficulties and contradictions. In Tali Tal and Iris Alkaher's, "Collaborative environmental projects in a multicultural society: Working from within separate or mutual landscapes?" the authors describe their efforts to do this in the highly charged…

  9. Mapping the Ancient Maya Landscape from Space

    NASA Technical Reports Server (NTRS)

    Sever, Tom

    2003-01-01

    This project uses new satellite and airborne imagery in combination with remote sensing, GIS, and GPS technology to understand the dynamics of how the Maya successfully interacted with their karst topographic landscape for several centuries in the northern Peten region of Guatemala. The ancient Maya attained one of the greatest population densities in human history in the tropical forest of the Peten, Guatemala, and it was in this region that the Maya civilization began, flourished, and abruptly disappeared for unknown reasons around AD 800. How the Maya were able to successfully manage water and feed this dense population is not known at this time. However, a recent NASA-funded project was the first to investigate large seasonal swamps (bajos) that make up 40 percent of the landscape. Through the use of remote sensing, ancient Maya features such as cities, roadways, canals and water reservoirs have been detected and verified through ground reconnaissance. The results of this research cast new light on the adaptation of the ancient Maya to their environment. Micro-environmental variation within the wetlands was elucidated and the different vegetational associations identified in the satellite imagery. More than 70 new archeological sites within and at the edges of the bajo were mapped and tested. Modification of the landscape by the Maya in the form of dams and reservoirs in the Holmul River and its tributaries and possible drainage canals in bajos was demonstrated. The recent acquisition of one-meter IKONOS imagery and high resolution STAR-3i radar imagery (2.5m backscatter/ 10m DEM), opens new possibilities for understanding how a civilization was able to survive for centuries upon a karst topographic landscape and their human-induced effects upon the local climate. This understanding is critical for the current population that is presently experiencing rapid population growth and destroying the landscape through non-traditional farming and grazing techniques

  10. Geomorphology of anthropogenic landscapes

    NASA Astrophysics Data System (ADS)

    Sofia, Giulia; Tarolli, Paolo

    2015-04-01

    The construction of urban areas and the development of road networks leave a significant signature on the Earth surface, providing a geomorphological evidence to support the idea that humans are nowadays a geomorphic agent having deep effects on the morphological organization of the landscape. The reconstruction or identification of anthropogenic topographies, therefore, provides a mechanism for quantifying anthropogenic changes to the landscape systems in the Anthropocene. Following this research line, the present study tests the effectiveness of a recently published topographic index, the Slope Local Length of Autocorrelation (SLLAC, Sofia et al. 2014) to portrait anthropogenic geomorphology, focusing in particular on road network density, and urban complexity (UCI). At first, the research considers the increasing of anthropic structures and the resulting changes in the SLLAC and in two derived parameters (mean SLLAC per km2 and SLLAC roughness, or Surface Peak Curvature -Spc). As a second step, considering the SLLAC derived indices, the anthropogenic geomorphology is automatically depicted using a k-means clustering algorithm. In general, the increasing of road network density or of the UCI is positively correlated to the mean SLLAC per km2, while the Spc is negatively correlated to the increasing of the anthropic structures. Areas presenting different road network organization are effectively captured considering multiple combinations of the defined parameters. Landscapes with small scattered towns, and a network with long roads in a dendritic shape (with hierarchical branching) are characterized simultaneously by high mean SLLAC and low Spc. Large and complex urban areas served by rectilinear networks with numerous short straight lines and right angles, have either a maximized mean SLLAC or a minimized Spc or both. In all cases, the anthropogenic landscape identified by the procedure is comparable to the ones identified manually from orthophoto, with the

  11. DNA sequence analysis using hierarchical ART-based classification networks

    SciTech Connect

    LeBlanc, C.; Hruska, S.I.; Katholi, C.R.; Unnasch, T.R.

    1994-12-31

    Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in real-time, and require no retraining to classify novel sequences. We have adapted ART networks to provide support to scientists attempting to categorize tandem repeat DNA fragments from Onchocerca volvulus. In this approach, sequences of DNA fragments are presented to multiple ART-based networks which are linked together into two (or more) tiers; the first provides coarse sequence classification while the sub- sequent tiers refine the classifications as needed. The overall rating of the resulting classification of fragments is measured using statistical techniques based on those introduced to validate results from traditional phylogenetic analysis. Tests of the Hierarchical ART-based Classification Network, or HABclass network, indicate its value as a fast, easy-to-use classification tool which adapts to new data without retraining on previously classified data.

  12. Link Dependent Adaptive Radio Simulation

    DTIC Science & Technology

    2014-06-01

    14. ABSTRACT This paper shows the optimized Link Dependent Adaptive Radio (LDAR) using the variable QAM OFDM modulation size which adapts to channel...bit error rate (BER), Orthogonal Frequency Division Multiplexing ( OFDM ) 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION OF ABSTRACT...using the variable QAM OFDM modulation size which adapts to channel conditions. The LDAR enhanced performance is illustrated by use of a flight path

  13. Using graph approach for managing connectivity in integrative landscape modelling

    NASA Astrophysics Data System (ADS)

    Rabotin, Michael; Fabre, Jean-Christophe; Libres, Aline; Lagacherie, Philippe; Crevoisier, David; Moussa, Roger

    2013-04-01

    FLUID-landr library has been developed in order i) to be used with no GIS expert skills needed (common gis formats can be read and simplified spatial management is provided), ii) to easily develop adapted rules of landscape discretization and graph creation to follow spatialized model requirements and iii) to allow model developers to manage dynamic and complex spatial topology. Graph management in OpenFLUID are shown with i) examples of hydrological modelizations on complex farmed landscapes and ii) the new implementation of Geo-MHYDAS tool based on the OpenFLUID-landr library, which allows to discretize a landscape and create graph structure for the MHYDAS model requirements.

  14. Optimization of Landscape Services under Uncoordinated Management by Multiple Landowners

    PubMed Central

    Porto, Miguel; Correia, Otília; Beja, Pedro

    2014-01-01

    objectives. It may thus be adapted to other socio-ecological systems, particularly where specific patterns of landscape heterogeneity are to be maintained despite imperfect management by multiple landowners. PMID:24465833

  15. An Object-Based Method for Chinese Landform Types Classification

    NASA Astrophysics Data System (ADS)

    Ding, Hu; Tao, Fei; Zhao, Wufan; Na, Jiaming; Tang, Guo'an

    2016-06-01

    Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM). In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

  16. A new multi-scale geomorphological landscape GIS for the Netherlands

    NASA Astrophysics Data System (ADS)

    Weerts, Henk; Kosian, Menne; Baas, Henk; Smit, Bjorn

    2013-04-01

    At present, the Cultural Heritage Agency of the Netherlands is developing a nationwide landscape Geographical Information System (GIS). In this new conceptual approach, the Agency puts together several multi-scale landscape classifications in a GIS. The natural physical landscapes lie at the basis of this GIS, because these landscapes provide the natural boundary conditions for anthropogenic. At the local scale a nationwide digital geomorphological GIS is available in the Netherlands. This map, that was originally mapped at 1:50,000 from the late 1970's to the 1990's, is based on geomorphometrical (observable and measurable in the field), geomorphological and, lithological and geochronological criteria. When used at a national scale, the legend of this comprehensive geomorphological map is very complex which hampers use in e.g. planning practice or predictive archaeology. At the national scale several landscape classifications have been in use in the Netherlands since the early 1950's, typically ranging in the order of 10 -15 landscape units for the entire country. A widely used regional predictive archaeological classification has 13 archaeo-landscapes. All these classifications have been defined "top-down" and their actual content and boundaries have only been broadly defined. Thus, these classifications have little or no meaning at a local scale. We have tried to combine the local scale with the national scale. To do so, we first defined national physical geographical regions based on the new 2010 national geological map 1:500,000. We also made sure there was a reference with the European LANMAP2 classification. We arrived at 20 landscape units at the national scale, based on (1) genesis, (2) large-scale geomorphology, (3) lithology of the shallow sub-surface and (4) age. These criteria that were chosen because the genesis of the landscape largely determines its (scale of) morphology and lithology that in turn determine hydrological conditions. All together

  17. Wildfire and landscape change

    USGS Publications Warehouse

    Santi, P.; Cannon, S.; DeGraff, J.

    2013-01-01

    Wildfire is a worldwide phenomenon that is expected to increase in extent and severity in the future, due to fuel accumulations, shifting land management practices, and climate change. It immediately affects the landscape by removing vegetation, depositing ash, influencing water-repellent soil formation, and physically weathering boulders and bedrock. These changes typically lead to increased erosion through sheetwash, rilling, dry ravel, and increased mass movement in the form of floods, debris flow, rockfall, and landslides. These process changes bring about landform changes as hillslopes are lowered and stream channels aggrade or incise at increased rates. Furthermore, development of alluvial fans, debris fans, and talus cones are enhanced. The window of disturbance to the landscape caused by wildfire is typically on the order of three to four years, with some effects persisting up to 30 years.

  18. Sharing a disparate landscape

    NASA Astrophysics Data System (ADS)

    Ali-Khan, Carolyne

    2010-06-01

    Working across boundaries of power, identity, and political geography is fraught with difficulties and contradictions. In Tali Tal and Iris Alkaher's, " Collaborative environmental projects in a multicultural society: Working from within separate or mutual landscapes?" the authors describe their efforts to do this in the highly charged atmosphere of Israel. This forum article offers a response to their efforts. Writing from a framework of critical pedagogy, I use the concepts of space and time to anchor my analysis, as I examine the issue of power in this Jew/Arab collaborative environmental project. This response problematizes "sharing" in a landscape fraught with disparities. It also looks to further Tal and Alkaher's work by geographically and politically grounding it in the broader current conflict and by juxtaposing sustainability with equity.

  19. Simulations of Fluvial Landscapes

    NASA Astrophysics Data System (ADS)

    Cattan, D.; Birnir, B.

    2013-12-01

    The Smith-Bretherton-Birnir (SBB) model for fluvial landsurfaces consists of a pair of partial differential equations, one governing water flow and one governing the sediment flow. Numerical solutions of these equations have been shown to provide realistic models in the evolution of fluvial landscapes. Further analysis of these equations shows that they possess scaling laws (Hack's Law) that are known to exist in nature. However, the simulations are highly dependent on the numerical methods used; with implicit methods exhibiting the correct scaling laws, but the explicit methods fail to do so. These equations, and the resulting models, help to bridge the gap between the deterministic and the stochastic theories of landscape evolution. Slight modifications of the SBB equations make the results of the model more realistic. By modifying the sediment flow equation, the model obtains more pronounced meandering rivers. Typical landsurface with rivers.

  20. Remote Sensing Information Classification

    NASA Technical Reports Server (NTRS)

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  1. Classification and knowledge

    NASA Technical Reports Server (NTRS)

    Kurtz, Michael J.

    1989-01-01

    Automated procedures to classify objects are discussed. The classification problem is reviewed, and the relation of epistemology and classification is considered. The classification of stellar spectra and of resolved images of galaxies is addressed.

  2. Astrobiological Landscape and Neocatastrophism

    NASA Astrophysics Data System (ADS)

    Cirkovic, M. M.; Vukotic, B.

    2009-09-01

    We review results of the simple 1-D models of the Galactic Habitable Zone constructed within neocatastrophic paradigm. The emerging astrobiological landscape demonstrates the capability of this theoretical framework to resolve the classical puzzles of Fermi's paradox and Carter's anthropic argument against extraterrestrial intelligence. Preliminary results show that astrobiology offers a clear rationale for the "Copernican" assumption of typicality of the age of the terrestrial biosphere.

  3. Classification of Physical Activity

    PubMed Central

    Turksoy, Kamuran; Paulino, Thiago Marques Luz; Zaharieva, Dessi P.; Yavelberg, Loren; Jamnik, Veronica; Riddell, Michael C.; Cinar, Ali

    2015-01-01

    Physical activity has a wide range of effects on glucose concentrations in type 1 diabetes (T1D) depending on the type (ie, aerobic, anaerobic, mixed) and duration of activity performed. This variability in glucose responses to physical activity makes the development of artificial pancreas (AP) systems challenging. Automatic detection of exercise type and intensity, and its classification as aerobic or anaerobic would provide valuable information to AP control algorithms. This can be achieved by using a multivariable AP approach where biometric variables are measured and reported to the AP at high frequency. We developed a classification system that identifies, in real time, the exercise intensity and its reliance on aerobic or anaerobic metabolism and tested this approach using clinical data collected from 5 persons with T1D and 3 individuals without T1D in a controlled laboratory setting using a variety of common types of physical activity. The classifier had an average sensitivity of 98.7% for physiological data collected over a range of exercise modalities and intensities in these subjects. The classifier will be added as a new module to the integrated multivariable adaptive AP system to enable the detection of aerobic and anaerobic exercise for enhancing the accuracy of insulin infusion strategies during and after exercise. PMID:26443291

  4. [Landscape character assessment framework in rural area: A case study in Qiaokou, Chang-sha, China].

    PubMed

    Zhang, Qian; Liu, Wen-ping; Yu, Zhen-rong

    2015-05-01

    Based on the concept and methods of landscape character assessment (LCA) in England, this paper applied a complete process of landscape character assessment with a case study in Qiaokou Town, which is located in a typical southern paddy fields area in Changsha City. We drew the landscape character map of Qiaokou Town through desk classification and field survey, identified and compared the key characters of each character area, and proposed suggestions on the improvement and stewardship of landscape characters. The results showed that Qiaokou could be divided into 2 landscape character types and 7 landscape character areas with the main differences in cropland and vegetation pattern as well as aesthetic characters. The case study indicated that LCA could be a critical tool to identify the characteristics in rural area, and provide helpful guidance to protect, restore and maintain the unique culture and characters of rural landscape, which is useful for targeted rural landscape development. In the future, we suggested that the assessment on the effects of landscape construction measures on the ecosystem services should be incorporated in LCA research as well.

  5. Characterizing biotic and abiotic properties of landscape and their implications for ecohydrological processes across scales

    NASA Astrophysics Data System (ADS)

    Kumar, J.; Langford, Z.; Hoffman, F. M.

    2015-12-01

    Ecohydrological processes governing the dynamics of terrestrial ecosystems and its response and feedback to climate change occur at diverse spatial and temporal scales. To accurately capture the dynamics of ecohydrological processes in the model, its critically important to capture the subgrid scale heterogeneity of the landscape and develop scale aware process representation and parameterization. This study focused on the Arctic tundra landscape at Seward Peninsula of Alaska. Ecohydrological processes in this sensitive landscape are strongly governed by the physical and structural properties (like topography, soil, permafrost, geomorphology etc.) of the landscape, environmental conditions (like temperature, precipitation, light, radiation) and biotic conditions (vegetation, above/below biomass and organic matter, disturbance history etc.). From site to watershed to regional (scale at which models often operate), landscape is a complex mosaic of a range of biotic and abiotic properties. We have developed and applied a hierarchical characterization and classification approach to segment the landscape in distinct units which can be used to develop and parameterize process models at local scale. We also analyze how the distribution and organization of the landscape units as building blocks influence and interact with ecosystem processes across scales. Our goals is understand the landscape organization principles and their roles to inform and improve process based models of ecohydrological processes in Arctic tundra landscape.

  6. Incorporating Bioenergy in Sustainable Landscape Designs Workshop Two: Agricultural Landscapes

    SciTech Connect

    Negri, M. Cristina; Ssegane, H.

    2015-08-01

    The Bioenergy Technologies Office hosted two workshops on Incorporating Bioenergy in Sustainable Landscape Designs with Oak Ridge and Argonne National Laboratories in 2014. The second workshop focused on agricultural landscapes and took place in Argonne, IL from June 24—26, 2014. The workshop brought together experts to discuss how landscape design can contribute to the deployment and assessment of sustainable bioenergy. This report summarizes the discussions that occurred at this particular workshop.

  7. Using multitemporal Landsat imagery to monitor and model the influences of landscape pattern on urban expansion in a metropolitan region

    NASA Astrophysics Data System (ADS)

    Yang, Yetao; Wong, Louis Ngai Yuen; Chen, Chao; Chen, Tao

    2014-01-01

    Studying the interaction between landscape patterns and temporal land-use changes in a metropolitan area can improve understanding of the urbanization process. Multitemporal remote sensing imagery is widely used to map the urbanization-caused temporal land-use dynamics, which mainly appear as built-up growth. Remote sensing integrated with landscape metrics is also used to quantitatively describe the landscape pattern of the urban area in recent literature. However, few studies have focused on the interaction between the pattern and the process of urbanization in a metropolitan area. We propose a grid-based framework to analyze the influence of the landscape pattern on the built-up growth by using the multitemporal Landsat imagery. Remote sensing classification method is used to obtain thematic land-use maps. Built-up growth is then extracted from the multitemporal classification results by a postclassification change detection. Landscape pattern, which is quantitatively described by landscape metrics, is derived from the thematic land-use maps. A grid-based method is used to analyze the spatial variation of landscape pattern and its related built-up growth. Finally, the spatial relationship between the landscape pattern and the built-up growth characters is assessed and modeled by using the mathematical regression method. The present study shows that an apparent correlation between landscape pattern and built-up growth exists. The correlation reflects the inherent influences of landscape pattern on urban expansion. The landscape pattern indicates the land development stage, while the urbanization stage determines the speed and style of the following built-up growth. Scales, including temporal scale and spatial scale, are important to modeling the landscape pattern effects on the built-up growth. The proposed analysis framework is efficient in detecting and modeling the landscape pattern effects on the built-up growth.

  8. Crop pathogen emergence and evolution in agro-ecological landscapes

    PubMed Central

    Papaïx, Julien; Burdon, Jeremy J; Zhan, Jiasui; Thrall, Peter H

    2015-01-01

    Remnant areas hosting natural vegetation in agricultural landscapes can impact the disease epidemiology and evolutionary dynamics of crop pathogens. However, the potential consequences for crop diseases of the composition, the spatial configuration and the persistence time of the agro-ecological interface – the area where crops and remnant vegetation are in contact – have been poorly studied. Here, we develop a demographic–genetic simulation model to study how the spatial and temporal distribution of remnant wild vegetation patches embedded in an agricultural landscape can drive the emergence of a crop pathogen and its subsequent specialization on the crop host. We found that landscape structures that promoted larger pathogen populations on the wild host facilitated the emergence of a crop pathogen, but such landscape structures also reduced the potential for the pathogen population to adapt to the crop. In addition, the evolutionary trajectory of the pathogen population was determined by interactions between the factors describing the landscape structure and those describing the pathogen life histories. Our study contributes to a better understanding of how the shift of land-use patterns in agricultural landscapes might influence crop diseases to provide predictive tools to evaluate management practices. PMID:25926883

  9. Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

    NASA Astrophysics Data System (ADS)

    Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

    2011-11-01

    The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

  10. The potential and flux landscape theory of evolution

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Xu, Li; Zhang, Kun; Wang, Erkang; Wang, Jin

    2012-08-01

    We established the potential and flux landscape theory for evolution. We found explicitly the conventional Wright's gradient adaptive landscape based on the mean fitness is inadequate to describe the general evolutionary dynamics. We show the intrinsic potential as being Lyapunov function(monotonically decreasing in time) does exist and can define the adaptive landscape for general evolution dynamics for studying global stability. The driving force determining the dynamics can be decomposed into gradient of potential landscape and curl probability flux. Non-zero flux causes detailed balance breaking and measures how far the evolution from equilibrium state. The gradient of intrinsic potential and curl flux are perpendicular to each other in zero fluctuation limit resembling electric and magnetic forces on electrons. We quantified intrinsic energy, entropy and free energy of evolution and constructed non-equilibrium thermodynamics. The intrinsic non-equilibrium free energy is a Lyapunov function. Both intrinsic potential and free energy can be used to quantify the global stability and robustness of evolution. We investigated an example of three allele evolutionary dynamics with frequency dependent selection (detailed balance broken). We uncovered the underlying single, triple, and limit cycle attractor landscapes. We found quantitative criterions for stability through landscape topography. We also quantified evolution pathways and found paths do not follow potential gradient and are irreversible due to non-zero flux. We generalized the original Fisher's fundamental theorem to the general (i.e., frequency dependent selection) regime of evolution by linking the adaptive rate with not only genetic variance related to the potential but also the flux. We show there is an optimum potential where curl flux resulting from biotic interactions of individuals within a species or between species can sustain an endless evolution even if the physical environment is unchanged. We

  11. Understanding patchy landscape dynamics: towards a landscape language.

    PubMed

    Gaucherel, Cédric; Boudon, Frédéric; Houet, Thomas; Castets, Mathieu; Godin, Christophe

    2012-01-01

    Patchy landscapes driven by human decisions and/or natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Systems, also called Formal Grammars. We used complicated scenarios of agricultural dynamics to model landscapes and to write their corresponding driving rule equations. Our second objective was to illustrate the relevance of this landscape language concept for landscape modelling through various grassland managements, with the final aim to assess their respective impacts on biological conservation. For this purpose, we made the assumptions that a higher grassland appearance frequency and higher land cover connectivity are favourable to species conservation. Ecological results revealed that dairy and beef livestock production systems are more favourable to wild species than is hog farming, although in different ways. Methodological results allowed us to efficiently model and formalize these landscape dynamics. This study demonstrates the applicability of the Rewriting System framework to the modelling of agricultural landscapes and, hopefully, to other patchy landscapes. The newly defined grammar is able to explain changes that are neither necessarily local nor Markovian, and opens a way to analytical modelling of landscape dynamics.

  12. Understanding Patchy Landscape Dynamics: Towards a Landscape Language

    PubMed Central

    Gaucherel, Cédric; Boudon, Frédéric; Houet, Thomas; Castets, Mathieu; Godin, Christophe

    2012-01-01

    Patchy landscapes driven by human decisions and/or natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Systems, also called Formal Grammars. We used complicated scenarios of agricultural dynamics to model landscapes and to write their corresponding driving rule equations. Our second objective was to illustrate the relevance of this landscape language concept for landscape modelling through various grassland managements, with the final aim to assess their respective impacts on biological conservation. For this purpose, we made the assumptions that a higher grassland appearance frequency and higher land cover connectivity are favourable to species conservation. Ecological results revealed that dairy and beef livestock production systems are more favourable to wild species than is hog farming, although in different ways. Methodological results allowed us to efficiently model and formalize these landscape dynamics. This study demonstrates the applicability of the Rewriting System framework to the modelling of agricultural landscapes and, hopefully, to other patchy landscapes. The newly defined grammar is able to explain changes that are neither necessarily local nor Markovian, and opens a way to analytical modelling of landscape dynamics. PMID:23049935

  13. Effects of landscape composition on edge-sensitive songbirds in a forest-dominated landscape

    SciTech Connect

    McRae, B.

    1995-12-31

    Thirty-eight mature upland forest stands in the Nicolet National Forest were selected to study relationships between abundances of edge-sensitive forest birds within the stands and patterning of vegetation types surrounding the stands. Ten indicator species were examined, and three years of point count data from the Nicolet National Forest Bird Survey formed the basis of the study. Three separate habitat maps were created to quantify landscape structural characteristics in a geographic information system (GIS); the first was compiled from existing vegetation inventory maps maintained by the Nicolet National Forest, the second was based on a Landsat Thematic Mapper satellite image classification, and the third was based on a combination of the first two habitat maps. Abundance of individuals in the indicator species group was related to statistical metrics of landscape pattern and proportions of habitat types surrounding the sites using multiple regression. Best subsets of variables to explain variation in total bird abundance were selected. Relationships between individual species abundances and landscape and site vegetation variables were also examined using univariate tests. The combined habitat mapping method provided the best regression model of songbird abundance, and relationships given by this model were consistent across all species.

  14. Estimating methane fluxes at a landscape scale

    NASA Astrophysics Data System (ADS)

    Stockdale, James; MacBean, Natasha

    2010-05-01

    Terrestrial methane fluxes are an important component of peatland carbon budgets. Using a well-studied peatland site in Wales as a case study, we present a variety of approaches to quantifying annual methane fluxes at a landscape scale, with a focus on the comparison between a simple stratification method, an empirical regression-based method and a process-based method. The simplest approach relies on in situ methane flux measurements which, due to the indirect effects on methane flux from the vascular transport mechanism and co-variation with hydrological conditions, were stratified by vegetation type. Aside from this initial classification, an annual landscape flux was produced through a linear scaling model without attempting to consider any physical, chemical or biological processes known to control methane fluxes. The regression-based approach attempted to model fluxes using repeated measurements from across the study site over a 12 months period, together with environmental variables from associated locations. This method classifies the landscape by vegetation in a similar way to the first method and also takes into consideration variables commonly known to influence methane flux such as temperature and water table. However, no direct consideration of methane production or consumption is included in this empirical regression model. In contrast to both the preceding methods, estimates of methane flux using a process-based model were constructed for the same landscape. This method uses the Carnegie-Ames-Stanford Approach (CASA) model (Potter et al., 1993), which has been modified to include a representation of methane dynamics. The model is calibrated with ground-based measurements of net CH4 flux and water table depth using a Metropolis Hastings Markov Chain Monte Carlo approach. Comparison of these approaches shows that, while simple methods of stratification and scaling are computationally inexpensive and quick to perform, they are least successful when

  15. Economic linkages to changing landscapes.

    PubMed

    Peterson, Jeffrey M; Caldas, Marcellus M; Bergtold, Jason S; Sturm, Belinda S; Graves, Russell W; Earnhart, Dietrich; Hanley, Eric A; Brown, J Christopher

    2014-01-01

    Many economic processes are intertwined with landscape change. A large number of individual economic decisions shape the landscape, and in turn the changes in the landscape shape economic decisions. This article describes key research questions about the economics of landscape change and reviews the state of research knowledge. The rich and varied economic-landscape interactions are an active area of research by economists, geographers, and others. Because the interactions are numerous and complex, disentangling the causal relationships in any given landscape system is a formidable research challenge. Limited data with mismatched temporal and spatial scales present further obstacles. Nevertheless, the growing body of economic research on these topics is advancing and shares fundamental challenges, as well as data and methods, with work in other disciplines.

  16. The concept of hydrologic landscapes

    USGS Publications Warehouse

    Winter, T.C.

    2001-01-01

    Hydrologic landscapes are multiples or variations of fundamental hydrologic landscape units. A fundamental hydrologic landscape unit is defined on the basis of land-surface form, geology, and climate. The basic land-surface form of a fundamental hydrologic landscape unit is an upland separated from a lowland by an intervening steeper slope. Fundamental hydrologic landscape units have a complete hydrologic system consisting of surface runoff, ground-water flow, and interaction with atmospheric water. By describing actual landscapes in terms of land-surface slope, hydraulic properties of soils and geologic framework, and the difference between precipitation and evapotranspiration, the hydrologic system of actual landscapes can be conceptualized in a uniform way. This conceptual framework can then be the foundation for design of studies and data networks, syntheses of information on local to national scales, and comparison of process research across small study units in a variety of settings. The Crow Wing River watershed in central Minnesota is used as an example of evaluating stream discharge in the context of hydrologic landscapes. Lake-research watersheds in Wisconsin, Minnesota, North Dakota, and Nebraska are used as an example of using the hydrologic-landscapes concept to evaluate the effect of ground water on the degree of mineralization and major-ion chemistry of lakes that lie within ground-water flow systems.

  17. Wind-Eroded Landscape

    NASA Technical Reports Server (NTRS)

    2005-01-01

    5 August 2005 This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows a dust-mantled, wind-eroded landscape in the Medusae Sulci region of Mars. Wind eroded the bedrock in this region, and then, later, windblown dust covered much of the terrain.

    Location near: 5.7oS, 160.2oW Image width: width: 3 km (1.9 mi) Illumination from: lower left Season: Southern Spring

  18. Probing the String Landscape

    SciTech Connect

    Keith Dienes

    2009-12-01

    We are currently in the throes of a potentially huge paradigm shift in physics. Motivated by recent developments in string theory and the discovery of the so-called "string landscape", physicists are beginning to question the uniqueness of fundamental theories of physics and the methods by which such theories might be understood and investigated. In this colloquium, I will give a non-technical introduction to the nature of this paradigm shift and how it developed. I will also discuss some of the questions to which it has led, and the nature of the controversies it has spawned.

  19. Stonehenge and its Landscape

    NASA Astrophysics Data System (ADS)

    Ruggles, Clive L. N.

    In the 1960s and 1970s, Stonehenge polarized academic opinion between those (mainly astronomers) who claimed it demonstrated great astronomical sophistication and those (mainly archaeologists) who denied it had anything to do with astronomy apart from the solstitial alignment of its main axis. Now, several decades later, links to the annual passage of the sun are generally recognized as an essential part of the function and meaning not only of Stonehenge but also of several other nearby monuments, giving us important insights into beliefs and actions relating to the seasonal cycle by the prehistoric communities who populated this chalkland landscape in the third millennium BC Links to the moon remain more debatable.

  20. Probing the String Landscape

    ScienceCinema

    Keith Dienes

    2016-07-12

    We are currently in the throes of a potentially huge paradigm shift in physics. Motivated by recent developments in string theory and the discovery of the so-called "string landscape", physicists are beginning to question the uniqueness of fundamental theories of physics and the methods by which such theories might be understood and investigated. In this colloquium, I will give a non-technical introduction to the nature of this paradigm shift and how it developed. I will also discuss some of the questions to which it has led, and the nature of the controversies it has spawned.

  1. A quantitative analysis of the grassland landscape pattern in arid oasis: a case study in the Qira

    NASA Astrophysics Data System (ADS)

    Ubul, Guljamal; Ding, Janli; Ruzi, Ahmatjan

    2008-10-01

    At present the remote sensing technology has become one of the most essential tools in the landscape ecology research. This paper is based on RS images from Landsat TM (1990), ETM (1999) and Aster (2004) imagery, with the support of RS and GIS technology and utilization of landscape ecology principle. Selected suitable image processing system, classification approaches and techniques and made a quantitative analysis of the study area's grassland landscape pattern change. RS image processing software (PCI) and landscape pattern analyzing software (Fragstats) is used in this article. The result shows that: in 1990, 1999 and 2004 the land use landscape pattern in study area experienced the considerable change. As far as the dynamic change of grassland landscape in the study area is concerned, natural factor takes certain driving action but human activities are the main driving force.

  2. THE EFFECTS OF HABITAT RESOLUTION ON MODELS OF AVIAN DIVERSITY AND DISTRIBUTIONS: A COMPARISON OF TWO LAND-COVER CLASSIFICATIONS

    EPA Science Inventory

    The quantification of pattern is a key element of landscape analyses. One aspect of this quantification of particular importance to landscape ecologists regards the classification of continuous variables to produce categorical variables such as land-cover type or elevation strat...

  3. Comparing Hydrogeomorphic Approaches to Lake Classification

    NASA Astrophysics Data System (ADS)

    Martin, Sherry L.; Soranno, Patricia A.; Bremigan, Mary T.; Cheruvelil, Kendra S.

    2011-11-01

    A classification system is often used to reduce the number of different ecosystem types that governmental agencies are charged with monitoring and managing. We compare the ability of several different hydrogeomorphic (HGM)—based classifications to group lakes for water chemistry/clarity. We ask: (1) Which approach to lake classification is most successful at classifying lakes for similar water chemistry/clarity? (2) Which HGM features are most strongly related to the lake classes? and, (3) Can a single classification successfully classify lakes for all of the water chemistry/clarity variables examined? We use univariate and multivariate classification and regression tree (CART and MvCART) analysis of HGM features to classify alkalinity, water color, Secchi, total nitrogen, total phosphorus, and chlorophyll a from 151 minimally disturbed lakes in Michigan USA. We developed two MvCART models overall and two CART models for each water chemistry/clarity variable, in each case comparing: local HGM characteristics alone and local HGM characteristics combined with regionalizations and landscape position. The combined CART models had the highest strength of evidence (ωi range 0.92-1.00) and maximized within class homogeneity (ICC range 36-66%) for all water chemistry/clarity variables except water color and chlorophyll a. Because the most successful single classification was on average 20% less successful in classifying other water chemistry/clarity variables, we found that no single classification captures variability for all lake responses tested. Therefore, we suggest that the most successful classification (1) is specific to individual response variables, and (2) incorporates information from multiple spatial scales (regionalization and local HGM variables).

  4. Adaptive processing for LANDSAT data

    NASA Technical Reports Server (NTRS)

    Crane, R. B.; Reyer, J. F.

    1975-01-01

    Analytical and test results on the use of adaptive processing on LANDSAT data are presented. The Kalman filter was used as a framework to contain different adapting techniques. When LANDSAT MSS data were used all of the modifications made to the Kalman filter performed the functions for which they were designed. It was found that adaptive processing could provide compensation for incorrect signature means, within limits. However, if the data were such that poor classification accuracy would be obtained when the correct means were used, then adaptive processing would not improve the accuracy and might well lower it even further.

  5. A novel modulation classification approach using Gabor filter network.

    PubMed

    Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

    2014-01-01

    A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel.

  6. A Novel Modulation Classification Approach Using Gabor Filter Network

    PubMed Central

    Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

    2014-01-01

    A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

  7. Landscape Evolution of Titan

    NASA Technical Reports Server (NTRS)

    Moore, Jeffrey

    2012-01-01

    Titan may have acquired its massive atmosphere relatively recently in solar system history. The warming sun may have been key to generating Titan's atmosphere over time, starting from a thin atmosphere with condensed surface volatiles like Triton, with increased luminosity releasing methane, and then large amounts of nitrogen (perhaps suddenly), into the atmosphere. This thick atmosphere, initially with much more methane than at present, resulted in global fluvial erosion that has over time retreated towards the poles with the removal of methane from the atmosphere. Basement rock, as manifested by bright, rough, ridges, scarps, crenulated blocks, or aligned massifs, mostly appears within 30 degrees of the equator. This landscape was intensely eroded by fluvial processes as evidenced by numerous valley systems, fan-like depositional features and regularly-spaced ridges (crenulated terrain). Much of this bedrock landscape, however, is mantled by dunes, suggesting that fluvial erosion no longer dominates in equatorial regions. High midlatitude regions on Titan exhibit dissected sedimentary plains at a number of localities, suggesting deposition (perhaps by sediment eroded from equatorial regions) followed by erosion. The polar regions are mainly dominated by deposits of fluvial and lacustrine sediment. Fluvial processes are active in polar areas as evidenced by alkane lakes and occasional cloud cover.

  8. Norwegian millstone quarry landscapes

    NASA Astrophysics Data System (ADS)

    Heldal, Tom; Meyer, Gurli; Grenne, Tor

    2013-04-01

    Rotary querns and millstones were used in Norway since just after the Roman Period until the last millstone was made in the 1930s. Throughout all this time millstone mining was fundamental for daily life: millstones were needed to grind grain, our most important food source. We can find millstone quarries in many places in the country from coast to mountain. Some of them cover many square kilometers and count hundreds of quarries as physical testimonies of a long and great production history. Other quarries are small and hardly visible. Some of this history is known through written and oral tradition, but most of it is hidden and must be reconstructed from the traces we can find in the landscape today. The Millstone project has put these quarry landscapes on the map, and conducted a range of case studies, including characterization of archaeological features connected to the quarrying, interpretation of quarrying techniques and evolution of such and establishing distribution and trade patterns by the aid of geological provenance. The project also turned out to be a successful cooperation between different disciplines, in particular geology and archaeology.

  9. The oxidation of landscapes

    NASA Astrophysics Data System (ADS)

    Rempe, D.; Hahm, W. J.; Dietrich, W. E.

    2015-12-01

    At the base of the critical zone, fresh rock is transformed through chemical alteration of minerals and fracturing. The resulting hydrologically dynamic weathered bedrock zone strongly influences how mass is routed throughout a landscape. Studies of weathering in a variety of lithologies and climates have documented the role of oxygen in driving the onset of weathering. Porosity is generated through processes such as the formation of sulfuric acid via oxidative pyrite dissolution and strain via iron oxidation in biotite. The transport of meteoric oxygen is therefore a mechanism that links the topographic surface to weathering processes at depth. Here, we present an alternative to the theory that the advance of an oxidation front is driven by downward advection and diffusion of meteoric fluid. We present field data and theory that suggest that the slow drainage of groundwater within fresh bedrock drives the displacement of unreactive pore fluid from low-porosity fresh bedrock. This drainage, and the subsequent introduction of meteoric fluid to fresh rock, is a hillslope scale process driven by channel incision. The resulting distribution of weathered rock across the landscape is thus controlled by the fresh bedrock porosity and permeability and the rate of channel incision.

  10. Landscapes Impacted by Light

    NASA Astrophysics Data System (ADS)

    Arellano, B.; Roca, J.

    2016-06-01

    The gradual spread of urbanization, the phenomenon known under the term urban sprawl, has become one of the paradigms that have characterized the urban development since the second half of the twentieth century and early twenty-first century. However, there is no unanimous consensus about what means "urbanization". The plurality of forms of human settlement on the planet difficult to identify the urbanization processes. The arrival of electrification to nearly every corner of the planet is certainly the first and more meaningful indicator of artificialization of land. In this sense, the paper proposes a new methodology based on the analysis of the satellite image of nighttime lights designed to identify the highly impacted landscapes worldwide and to build an index of Land Impacted by Light per capita (LILpc) as an indicator of the level of urbanization. The used methodology allows the identification of different typologies of urbanized areas (villages, cities or metropolitan areas), as well as "rural", "rurban", "periurban" and "central" landscapes. The study identifies 186,134 illuminated contours (urbanized areas). In one hand, 404 of these contours could be consider as real "metropolitan areas"; and in the other hand, there are 161,821 contours with less than 5,000 inhabitants, which could be identify as "villages". Finally, the paper shows that 44.5 % live in rural areas, 15.5 % in rurban spaces, 26.2 % in suburban areas and only 18.4 % in central areas.

  11. Intrinsically Disordered Energy Landscapes

    NASA Astrophysics Data System (ADS)

    Chebaro, Yassmine; Ballard, Andrew J.; Chakraborty, Debayan; Wales, David J.

    2015-05-01

    Analysis of an intrinsically disordered protein (IDP) reveals an underlying multifunnel structure for the energy landscape. We suggest that such ‘intrinsically disordered’ landscapes, with a number of very different competing low-energy structures, are likely to characterise IDPs, and provide a useful way to address their properties. In particular, IDPs are present in many cellular protein interaction networks, and several questions arise regarding how they bind to partners. Are conformations resembling the bound structure selected for binding, or does further folding occur on binding the partner in a induced-fit fashion? We focus on the p53 upregulated modulator of apoptosis (PUMA) protein, which adopts an -helical conformation when bound to its partner, and is involved in the activation of apoptosis. Recent experimental evidence shows that folding is not necessary for binding, and supports an induced-fit mechanism. Using a variety of computational approaches we deduce the molecular mechanism behind the instability of the PUMA peptide as a helix in isolation. We find significant barriers between partially folded states and the helix. Our results show that the favoured conformations are molten-globule like, stabilised by charged and hydrophobic contacts, with structures resembling the bound state relatively unpopulated in equilibrium.

  12. Intrinsically Disordered Energy Landscapes

    PubMed Central

    Chebaro, Yassmine; Ballard, Andrew J.; Chakraborty, Debayan; Wales, David J.

    2015-01-01

    Analysis of an intrinsically disordered protein (IDP) reveals an underlying multifunnel structure for the energy landscape. We suggest that such ‘intrinsically disordered’ landscapes, with a number of very different competing low-energy structures, are likely to characterise IDPs, and provide a useful way to address their properties. In particular, IDPs are present in many cellular protein interaction networks, and several questions arise regarding how they bind to partners. Are conformations resembling the bound structure selected for binding, or does further folding occur on binding the partner in a induced-fit fashion? We focus on the p53 upregulated modulator of apoptosis (PUMA) protein, which adopts an -helical conformation when bound to its partner, and is involved in the activation of apoptosis. Recent experimental evidence shows that folding is not necessary for binding, and supports an induced-fit mechanism. Using a variety of computational approaches we deduce the molecular mechanism behind the instability of the PUMA peptide as a helix in isolation. We find significant barriers between partially folded states and the helix. Our results show that the favoured conformations are molten-globule like, stabilised by charged and hydrophobic contacts, with structures resembling the bound state relatively unpopulated in equilibrium. PMID:25999294

  13. Sustainability, Smart Growth, and Landscape Architecture

    EPA Pesticide Factsheets

    Sustainability, Smart Growth, and Landscape Architecture is an overview course for landscape architecture students interested in sustainability in landscape architecture and how it might apply to smart growth principles in urban, suburban, and rural areas

  14. GOATS 2008 Autonomous, Adaptive Multistatic Acoustic Sensing

    DTIC Science & Technology

    2008-09-30

    adaptive, bi- and multi-static, passive and active sonar configurations for concurrent detection, classification and localization of subsea and bottom...classification and localization of subsea and bottom objects.. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as...very shallow water (VSW). The fundamental approach of GOATS is the development of the concept of a network of AUVs as an array of Virtual Sensors

  15. Landscaping With Maintenance in Mind.

    ERIC Educational Resources Information Center

    Sorensen, Randy

    2000-01-01

    Examines school ground landscape design that enhances attractive of the school and provides for easier maintenance. Landscape design issues discussed include choice of grass, trees, and shrubs; irrigation; and safety and access. Other considerations for lessening maintenance problems for facility managers are also highlighted. (GR)

  16. Landscape Solutions to School Problems.

    ERIC Educational Resources Information Center

    Spitz, Katherine

    2002-01-01

    Discusses key lessons in school landscape design. Landscapes should: (1) include trees and plants that themselves provide hands-on teaching opportunities; (2) enhance health and safety in a number of ways while performing their other functions; (3) be sensitively designed relative to location to cut energy costs; and (4) be aesthetic as well as…

  17. Complex Landscape Terms in Seri

    ERIC Educational Resources Information Center

    O'Meara, Carolyn; Bohnemeyer, Jurgen

    2008-01-01

    The nominal lexicon of Seri is characterized by a prevalence of analytical descriptive terms. We explore the consequences of this typological trait in the landscape domain. The complex landscape terms of Seri classify geographic entities in terms of their material make-up and spatial properties such as shape, orientation, and merological…

  18. Landscape in a Lacquer Box

    ERIC Educational Resources Information Center

    Savage, Martha

    2010-01-01

    A symbolic dry landscape garden of Eastern origin holds a special fascination for the author's middle-school students, which is why the author chose to create a project exploring this view of nature. A dry landscape garden, or "karesansui," is an arrangement of rocks, worn by nature and surrounded by a "sea" of sand, raked into patterns…

  19. Fantasy Landscapes with a Message

    ERIC Educational Resources Information Center

    D'Amico, Elizabeth

    2005-01-01

    The author of this article describes using a Fantasy Landscapes lesson to get students expressing environmental issues through art. The Fantasy Landscapes lesson is an exploration of art elements and design principles through visual problem solving that links ideas, language, and theory to art. To get students thinking specifically about…

  20. I-CAN: The Classification and Prediction of Support Needs

    ERIC Educational Resources Information Center

    Arnold, Samuel R. C.; Riches, Vivienne C.; Stancliffe, Roger J.

    2014-01-01

    Background: Since 1992, the diagnosis and classification of intellectual disability has been dependent upon three constructs: intelligence, adaptive behaviour and support needs (Luckasson "et al." 1992. Mental Retardation: Definition, Classification and Systems of Support. American Association on Intellectual and Developmental…

  1. Using community archetypes to better understand differential community adaptation to wildfire risk.

    PubMed

    Carroll, Matthew; Paveglio, Travis

    2016-06-05

    One of the immediate challenges of wildfire management concerns threats to human safety and property in residential areas adjacent to non-cultivated vegetation. One approach for relieving this problem is to increase human community 'adaptiveness' to deal with the risk and reality of fire in a variety of landscapes. The challenge in creating 'fire-adapted communities' (FACs) is the great diversity in character and make-up of populations at risk from wildfire. This paper outlines a recently developed categorization scheme for Wildland-Urban Interface (WUI) communities based on a larger conceptual approach for understanding how social diversity is likely to influence the creation of FACs. The WUI categorization scheme situates four community archetypes on a continuum that recognizes dynamic change in human community functioning. We use results from the WUI classification scheme to outline key characteristics associated with each archetype and results from recent case studies to demonstrate the diversity across WUI communities. Differences among key characteristics of local social context will likely result in the need for different adaptation strategies to wildfire. While the WUI archetypes described here may not be broadly applicable to other parts of the world, we argue that the conceptual approach and strategies for systematically documenting local influences on wildfire adaptation have potential for broad application.This article is part of the themed issue 'The interaction of fire and mankind'.

  2. Genomic Classification of Cutaneous Melanoma.

    PubMed

    2015-06-18

    We describe the landscape of genomic alterations in cutaneous melanomas through DNA, RNA, and protein-based analysis of 333 primary and/or metastatic melanomas from 331 patients. We establish a framework for genomic classification into one of four subtypes based on the pattern of the most prevalent significantly mutated genes: mutant BRAF, mutant RAS, mutant NF1, and Triple-WT (wild-type). Integrative analysis reveals enrichment of KIT mutations and focal amplifications and complex structural rearrangements as a feature of the Triple-WT subtype. We found no significant outcome correlation with genomic classification, but samples assigned a transcriptomic subclass enriched for immune gene expression associated with lymphocyte infiltrate on pathology review and high LCK protein expression, a T cell marker, were associated with improved patient survival. This clinicopathological and multi-dimensional analysis suggests that the prognosis of melanoma patients with regional metastases is influenced by tumor stroma immunobiology, offering insights to further personalize therapeutic decision-making.

  3. Landscape structure affects specialists but not generalists in naturally fragmented grasslands

    USGS Publications Warehouse

    Miller, Jesse E.D.; Damschen, Ellen Ingman; Harrison, Susan P.; Grace, James B.

    2015-01-01

    Understanding how biotic communities respond to landscape spatial structure is critically important for conservation management as natural landscapes become increasingly fragmented. However, empirical studies of the effects of spatial structure on plant species richness have found inconsistent results, suggesting that more comprehensive approaches are needed. In this study, we asked how landscape structure affects total plant species richness and the richness of a guild of specialized plants in a multivariate context. We sampled herbaceous plant communities at 56 dolomite glades (insular, fire-adapted grasslands) across the Missouri Ozarks, and used structural equation modeling (SEM) to analyze the relative importance of landscape structure, soil resource availability, and fire history for plant communities. We found that landscape spatial structure-defined as the area-weighted proximity of glade habitat surrounding study sites (proximity index)-had a significant effect on total plant species richness, but only after we controlled for environmental covariates. Richness of specialist species, but not generalists, was positively related to landscape spatial structure. Our results highlight that local environmental filters must be considered to understand the influence of landscape structure on communities, and that unique species guilds may respond differently to landscape structure than the community as a whole. These findings suggest that both local environment and landscape context should be considered when developing management strategies for species of conservation concern in fragmented habitats.

  4. Management and development of land in the name of the Green Economy: planning, landscape, efficiency, biodiversity

    NASA Astrophysics Data System (ADS)

    Benvenuti, Paolo

    2016-04-01

    preservation of landscapes; • relationship between the wine areas with the territory and its infrastructure; • participation in the process of territorial planning with operators and administrations; • relationship between wine and landscape, adaptation to climatic deterioration, renewable energy sources and energy efficiency; • new skills and new forms to manage the vineyard Depth knowledge of the characteristics of the territory wine passes through: • wine zoning, i.e. the identification of the more suitable terroirs for a wine: study of the climate, the soil, the vines of the interactions with the environment (Chart of vocations agroforestry); • soil classification; • analysis of the ecosystems (flora and fauna, biodiversity, forest, grasslands, crops); • identification of landscapes, from the analysis of types, morphology of the urban and rural landscape, processes of contextualization, etc. (Chart of landscape values) . The results achieved so far by the Italian municipalities that have adopted them, will soon be enhanced by enlargement of the methodological lines to new issues such as accessibility in wine territory, strengthening of local participation and the presence, promotion of wine as an integral part the local food planning, development of planning practices in the process of institutional reform.

  5. On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  6. On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  7. Issues in using landscape indicators to assess land changes

    SciTech Connect

    Kline, Keith L; Dale, Virginia H

    2012-01-01

    Landscape indicators, when combined with information about environmental conditions (such as habitat potential, biodiversity, carbon and nutrient cycling, and erosion) and socioeconomic forces, can provide insights about changing ecosystem services. They also provide information about opportunities for improving natural resources management. Landscape indicators rely on data regarding land cover, land management and land functionality. Challenges in using landscape indicators to assess change and effects include (1) measures of land management and attributes that are reliable, robust and consistent for all areas on the Earth do not exist, and thus land cover is more frequently utilized; (2) multiple types of land cover and management are often found within a single landscape and are constantly changing, which complicates measurement and interpretation; and (3) while causal analysis is essential for understanding and interpreting changes in indicator values, the interactions among multiple causes and effects over time make accurate attribution among many drivers of change particularly difficult. Because of the complexity, sheer number of variables, and limitations of empirical data on land changes, models are often used to illustrate and estimate values for landscape indicators, and those models have several problems. Recommendations to improve our ability to assess the effects of changes in land management include refinement of questions to be more consistent with available information and the development of data sets based on systematic measurement over time of spatially explicit land qualities such as carbon and nutrient stocks, water and soil quality, net primary productivity, habitat and biodiversity. Well-defined and consistent land-classification systems that are capable of tracking changes in these and other qualities that matter to society need to be developed and deployed. Because landscapes are so dynamic, it is crucial to develop ways for the scientific

  8. Modelling vegetated dune landscapes

    NASA Astrophysics Data System (ADS)

    Baas, A. C. W.; Nield, J. M.

    2007-03-01

    This letter presents a self-organising cellular automaton model capable of simulating the evolution of vegetated dunes with multiple types of plant response in the environment. It can successfully replicate hairpin, or long-walled, parabolic dunes with trailing ridges as well as nebkha dunes with distinctive deposition tails. Quantification of simulated landscapes with eco-geomorphic state variables and subsequent cluster analysis and PCA yields a phase diagram of different types of coastal dunes developing from blow-outs as a function of vegetation vitality. This diagram indicates the potential sensitivity of dormant dune fields to reactivation under declining vegetation vitality, e.g. due to climatic changes. Nebkha simulations with different grid resolutions demonstrate that the interaction between the (abiotic) geomorphic processes and the biological vegetation component (life) introduces a characteristic length scale on the resultant landforms that breaks the typical self-similar scaling of (un-vegetated) bare-sand dunes.

  9. Buildings Interoperability Landscape

    SciTech Connect

    Hardin, Dave; Stephan, Eric G.; Wang, Weimin; Corbin, Charles D.; Widergren, Steven E.

    2015-12-31

    Through its Building Technologies Office (BTO), the United States Department of Energy’s Office of Energy Efficiency and Renewable Energy (DOE-EERE) is sponsoring an effort to advance interoperability for the integration of intelligent buildings equipment and automation systems, understanding the importance of integration frameworks and product ecosystems to this cause. This is important to BTO’s mission to enhance energy efficiency and save energy for economic and environmental purposes. For connected buildings ecosystems of products and services from various manufacturers to flourish, the ICT aspects of the equipment need to integrate and operate simply and reliably. Within the concepts of interoperability lie the specification, development, and certification of equipment with standards-based interfaces that connect and work. Beyond this, a healthy community of stakeholders that contribute to and use interoperability work products must be developed. On May 1, 2014, the DOE convened a technical meeting to take stock of the current state of interoperability of connected equipment and systems in buildings. Several insights from that meeting helped facilitate a draft description of the landscape of interoperability for connected buildings, which focuses mainly on small and medium commercial buildings. This document revises the February 2015 landscape document to address reviewer comments, incorporate important insights from the Buildings Interoperability Vision technical meeting, and capture thoughts from that meeting about the topics to be addressed in a buildings interoperability vision. In particular, greater attention is paid to the state of information modeling in buildings and the great potential for near-term benefits in this area from progress and community alignment.

  10. Evolutionary advantage of small populations on complex fitness landscapes.

    PubMed

    Jain, Kavita; Krug, Joachim; Park, Su-Chan

    2011-07-01

    Recent experimental and theoretical studies have shown that small asexual populations evolving on complex fitness landscapes may achieve a higher fitness than large ones due to the increased heterogeneity of adaptive trajectories. Here, we introduce a class of haploid three-locus fitness landscapes that allow the investigation of this scenario in a precise and quantitative way. Our main result derived analytically shows how the probability of choosing the path of the largest initial fitness increase grows with the population size. This makes large populations more likely to get trapped at local fitness peaks and implies an advantage of small populations at intermediate time scales. The range of population sizes where this effect is operative coincides with the onset of clonal interference. Additional studies using ensembles of random fitness landscapes show that the results achieved for a particular choice of three-locus landscape parameters are robust and also persist as the number of loci increases. Our study indicates that an advantage for small populations is likely whenever the fitness landscape contains local maxima. The advantage appears at intermediate time scales, which are long enough for trapping at local fitness maxima to have occurred but too short for peak escape by the creation of multiple mutants.

  11. Connecting Managers and Scientists Through the California Landscape Conservation Cooperative

    NASA Astrophysics Data System (ADS)

    Ballard, G.; Schlafmann, D.

    2015-12-01

    The science-management partnership of the California Landscape Conservation Cooperative (CA LCC) works to address the landscape-scale impacts of climate change on California's ecosystems. This presentation focuses on models of successful science translation and co-production demonstrated by Point Blue Conservation Science, a member of the CA LCC. These models have all brought scientists and managers together for the common goal of integrating climate science into natural resource management decisions. These efforts include the intentional and deliberate consideration of climate change, addressing both mitigation and adaptation, referred to as Climate-Smart Conservation. These Climate-Smart Conservation efforts are strengthened through collaboratively adopting forward-looking goals and explicitly linking strategies to key climate impacts and vulnerabilities. Successes include integrating climate modeling into decision making and planning efforts, establishment of citizen science networks that inform management actions, and collaborative development of climate adaptation strategies with natural resource managers from the Sierra to the sea.

  12. Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints

    PubMed Central

    Chan, Yvonne H.; Venev, Sergey V.; Zeldovich, Konstantin B.; Matthews, C. Robert

    2017-01-01

    Sequence divergence of orthologous proteins enables adaptation to environmental stresses and promotes evolution of novel functions. Limits on evolution imposed by constraints on sequence and structure were explored using a model TIM barrel protein, indole-3-glycerol phosphate synthase (IGPS). Fitness effects of point mutations in three phylogenetically divergent IGPS proteins during adaptation to temperature stress were probed by auxotrophic complementation of yeast with prokaryotic, thermophilic IGPS. Analysis of beneficial mutations pointed to an unexpected, long-range allosteric pathway towards the active site of the protein. Significant correlations between the fitness landscapes of distant orthologues implicate both sequence and structure as primary forces in defining the TIM barrel fitness landscape and suggest that fitness landscapes can be translocated in sequence space. Exploration of fitness landscapes in the context of a protein fold provides a strategy for elucidating the sequence-structure-fitness relationships in other common motifs. PMID:28262665

  13. Landscape characterization and biodiversity research

    SciTech Connect

    Dale, V.H.; Offerman, H.; Frohn, R.; Gardner, R.H.

    1995-03-01

    Rapid deforestation often produces landscape-level changes in forest characteristics and structure, including area, distribution, and forest habitat types. Changes in landscape pattern through fragmentation or aggregation of natural habitats can alter patterns of abundance for single species and entire communities. Examples of single-species effects include increased predation along the forest edge, the decline in the number of species with poor dispersal mechanisms, and the spread of exotic species that have deleterious effects (e.g., gypsy moth). A decrease in the size and number of natural habitat patches increases the probability of local extirpation and loss of diversity of native species, whereas a decline in connectivity between habitat patches can negatively affect species persistence. Thus, there is empirical justification for managing entire landscapes, not just individual habitat types, in order to insure that native plant and animal diversity is maintained. A landscape is defined as an area composed of a mosaic of interacting ecosystems, or patches, with the heterogeneity among the patches significantly affecting biotic and abiotic processes in the landscape. Patches comprising a landscape are usually composed of discrete areas of relatively homogeneous environmental conditions and must be defined in terms of the organisms of interest. A large body of theoretical work in landscape ecology has provided a wealth of methods for quantifying spatial characteristics of landscapes. Recent advances in remote sensing and geographic information systems allow these methods to be applied over large areas. The objectives of this paper are to present a brief overview of common measures of landscape characteristics, to explore the new technology available for their calculation, to provide examples of their application, and to call attention to the need for collection of spatially-explicit field data.

  14. How soil shapes the landscape

    NASA Astrophysics Data System (ADS)

    Minasny, Budiman; Finke, Peter; Vanwalleghem, Tom Tom; Stockmann, Uta; McBratney, Alex

    2014-05-01

    There has been an increase in interest in quantitative modelling of soil genesis, which can provide prediction of environmental changes through numerical models. Modelling soil formation is a difficult task because soil itself is highly complex with interactions between water, inorganic materials and organic matter. This paper will provide a review on the research efforts of modelling soil genesis, their connection with landscape models and the inexorable genesis of the IUSS soil landscape modelling working group. Quantitative modelling soil formation using mechanistic models have begun in the 1980s such as the 'soil deficit' model by Kirkby (1985), Hoosbeek & Bryant's pedodynamic model (1992), and recently the SoilGen model by Finke (2008). These profile models considered the chemical reactions and physical processes in the soil at the horizon and pedon scale. The SoilGen model is an integration of sub-models, such as water and solute movement, heat transport, soil organic matter decomposition, mineral dissolution, ion exchange, adsorption, speciation, complexation and precipitation. The model can calculate with detail the chemical changes and materials fluxes in a profile and has been successfully applied. While they can simulate soil profile development in detail, there is still a gap how the processes act in the landscape. Meanwhile research in landscape formation in geomorphology is progressing steadily over time, slope development models model have been developed since 1970s (Ahnert, 1977). Soil was also introduced in a landscape, however soil processes are mainly modelled through weathering and transport processes (Minasny & McBratney 1999, 2001). Recently, Vanwalleghem et al. (2013) are able to combine selected physical, chemical and biological processes to simulate a full 3-D soil genesis in the landscape. Now there are research gaps between the 2 approaches: the landscape modellers increasingly recognise the importance of soil and need more detailed soil

  15. Decision making on fitness landscapes

    NASA Astrophysics Data System (ADS)

    Arthur, R.; Sibani, P.

    2017-04-01

    We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.

  16. Comparing classification methods for longitudinal fMRI studies.

    PubMed

    Schmah, Tanya; Yourganov, Grigori; Zemel, Richard S; Hinton, Geoffrey E; Small, Steven L; Strother, Stephen C

    2010-11-01

    We compare 10 methods of classifying fMRI volumes by applying them to data from a longitudinal study of stroke recovery: adaptive Fisher's linear and quadratic discriminant; gaussian naive Bayes; support vector machines with linear, quadratic, and radial basis function (RBF) kernels; logistic regression; two novel methods based on pairs of restricted Boltzmann machines (RBM); and K-nearest neighbors. All methods were tested on three binary classification tasks, and their out-of-sample classification accuracies are compared. The relative performance of the methods varies considerably across subjects and classification tasks. The best overall performers were adaptive quadratic discriminant, support vector machines with RBF kernels, and generatively trained pairs of RBMs.

  17. Classification Shell Game.

    ERIC Educational Resources Information Center

    Etzold, Carol

    1983-01-01

    Discusses shell classification exercises. Through keying students advanced from the "I know what a shell looks like" stage to become involved in the classification process: observing, labeling, making decisions about categories, and identifying marine animals. (Author/JN)

  18. Connecting Brabant's cover sand landscapes through landscape history

    NASA Astrophysics Data System (ADS)

    Heskes, Erik; van den Ancker, Hanneke; Jungerius, Pieter Dirk; Harthoorn, Jaap; Maes, Bert; Leenders, Karel; de Jongh, Piet; Kluiving, Sjoerd; van den Oetelaar, Ger

    2015-04-01

    Noord-Brabant has the largest variety of cover sand landscapes in The Netherlands, and probably in Western Europe. During the Last Ice Age the area was not covered by land ice and a polar desert developed in which sand dunes buried the existing river landscapes. Some of these polar dune landscapes experienced a geomorphological and soil development that remained virtually untouched up to the present day, such as the low parabolic dunes of the Strabrechtse Heide or the later and higher dunes of the Oisterwijkse Vennen. As Noord-Brabant lies on the fringe of a tectonic basin, the thickness of cover sand deposits in the Centrale Slenk, part of a rift through Europe, amounts up to 20 metres. Cover sand deposits along the fault lines cause the special phenomenon of 'wijst' to develop, in which the higher grounds are wetter than the boarding lower grounds. Since 4000 BC humans settled in these cover sand landscapes and made use of its small-scale variety. An example are the prehistoric finds on the flanks and the historic towns on top of the 'donken' in northwest Noord-Brabant, where the cover sand landscapes are buried by river and marine deposits and only the peaks of the dunes protrude as donken. Or the church of Handel that is built beside a 'wijst' source and a site of pilgrimage since living memory. Or the 'essen' and plaggen agriculture that developed along the stream valleys of Noord-Brabant from 1300 AD onwards, giving rise to geomorphological features as 'randwallen' and plaggen soils of more than a metre thickness. Each region of Brabant each has its own approach in attracting tourists and has not yet used this common landscape history to connect, manage and promote their territories. We propose a landscape-historical approach to develop a national or European Geopark Brabants' cover sand landscapes, in which each region focuses on a specific part of the landscape history of Brabant, that stretches from the Late Weichselian polar desert when the dune

  19. RS- and GIS-based study on landscape pattern change in the Poyang Lake wetland area, China

    NASA Astrophysics Data System (ADS)

    Chen, Xiaoling; Li, Hui; Bao, Shuming; Wu, Zhongyi; Fu, Weijuan; Cai, Xiaobin; Zhao, Hongmei; Guo, Peng

    2006-10-01

    As wetland has been recognized as an important component of ecosystem, it is received ever-increasing attention worldwide. Poyang Lake wetlands, the international wetlands and the largest bird habitat in Asia, play an important role in biodiversity and ecologic protection. However, with the rapid economic growth and urbanization, landscape patterns in the wetlands have dramatically changed in the past three decades. To better understand the wetland landscape dynamics, remote sensing, geographic information system technologies, and the FRAGSTATS landscape analysis program were used to measure landscape patterns. Statistical approach was employed to illustrate the driving forces. In this study, Landsat images (TM and ETM+) from 1989 and 2000 were acquired for the wetland area. The landscapes in the wetland area were classified as agricultural land, urban, wetland, forest, grassland, unused land, and water body using a combination of supervised and unsupervised classification techniques integrated with Digital Elevation Model (DEM). Landscape indices, which are popular for the quantitative analysis of landscape pattern, were then employed to analyze the landscape pattern changes between the two dates in a GIS. From this analysis an understanding of the spatial-temporal patterns of landscape evolution was generated. The results show that wetland area was reduced while fragmentation was increased over the study period. Further investigation was made to examine the relationship between landscape metrics and some other parameters such as urbanization to address the driving forces for those changes. The urban was chosen as center to conduct buffer analysis in a GIS to study the impact of human-induced activities on landscape pattern dynamics. It was found that the selected parameters were significantly correlated with the landscape metrics, which may well indicate the impact of human-induced activities on the wetland landscape pattern dynamics and account for the driving

  20. Assessment of land use and land cover change using spatiotemporal analysis of landscape: case study in south of Tehran.

    PubMed

    Sabr, Abutaleb; Moeinaddini, Mazaher; Azarnivand, Hossein; Guinot, Benjamin

    2016-12-01

    In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.

  1. Energy landscapes for machine learning.

    PubMed

    Ballard, Andrew J; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D; Wales, David J

    2017-04-03

    Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

  2. Economic Growth and Landscape Change

    USGS Publications Warehouse

    Prato, Tony; Fagre, Dan

    2007-01-01

    Sustaining Rocky Mountain Landscapes provides a scientific basis for communities to develop policies for managing the growth and economic transformation of the CCE without sacrificing the quality of life and environment for which the land is renowned. This forthcoming edited volume focuses on five aspects of sustaining mountain landscapes in the CCE and similar regions in the Rocky Mountains. The five aspects are: 1) how social, economic, demographic and environmental forces are transforming ecosystem structure and function, 2) trends in use and conditions for human and environmental resources, 3) activating science, policy and education to enhance sustainable landscape management, 4) challenges to sustainable management of public and private lands, and 5) future prospects for achieving sustainable landscapes.

  3. LANDSCAPE CORRELATES TO ESTUARINE CONDITION

    EPA Science Inventory

    Estuaries are important transition zones between land and sea, yet little is known about how landscapes influence these systems. Using broad scale Environmental Monitoring and Assessment Program (EMAP) data collected in small estuaries of the Virginian Biogeographic Province, w...

  4. Mapping resource use over a Russian landscape: an integrated look at harvesting of a non-timber forest product in central Kamchatka

    NASA Astrophysics Data System (ADS)

    Hitztaler, Stephanie K.; Bergen, Kathleen M.

    2013-12-01

    Small-scale resource use became an important adaptive mechanism in remote logging communities in Russia at the onset of the post-Soviet period in 1991. We focused on harvesting of a non-timber forest product, lingonberry (Vaccinium vitis-idaea), in the forests of the Kamchatka Peninsula (Russian Far East). We employed an integrated geographical approach to make quantifiable connections between harvesting and the landscape, and to interpret these relationships in their broader contexts. Landsat TM images were used for a new classification; the resulting land-cover map was the basis for linking non-spatial data on harvesters’ gathering behaviors to spatial data within delineated lingonberry gathering sites. Several significant relationships emerged: (1) mature forests negatively affected harvesters’ initial choice to gather in a site, while young forests had a positive effect; (2) land-cover type was critical in determining how and why gathering occurred: post-disturbance young and maturing forests were significantly associated with higher gathering intensity and with the choice to market harvests; and (3) distance from gathering sites to villages and main roads also mattered: longer distances were significantly correlated to more time spent gathering and to increased marketing of harvests. We further considered our findings in light of the larger ecological and social dynamics at play in central Kamchatka. This unique study is an important starting point for conservation- and sustainable development-based work, and for additional research into the drivers of human-landscape interactions in the Russian Far East.

  5. Planetary landscape: a new synthesis

    NASA Astrophysics Data System (ADS)

    Hargitai, H.

    The elements that build up a landscape on Earth consists of natural (biogenic and abiogenic - lithologic, atmospheric, hydrologic) and artificial (antropogenic) factors. Landscape is a complex system of these different elements, which interact with one another. For example the same lithology makes different landscapes under different climatic conditions. If the same conditions are present, the same landscape type will appear. The mosaic of ecotopes (topical) units, which are the system of homogenous caharacteristic areas of various geotopes makes up different level geochores (chorical unit). Geochores build up a hierarchic system and cover the whole surface.On Earth, landscapes can be qualified according to their characteristics: relief forms (morphology), and its potential economic value. Aesthetic and subjective parameters can also be considered especially when speaking of a residental area. We now propose the determination of "planetary landscape sets" which can potentially occur on the solid surface of a planetary body during its lifetime. This naturally includes landscapes of the present state of planetary bodies and also paleolandscapes from the past of planets, including Earth. Landscapes occur in the boundary of the planets solid and not solid sphere that is on the solid-vacuum, the solid - gas and on the solid - liquid boundary. Thinking this way a landscape can occurs on the ocean floor as well. We found that for the determination of a planetary landscape system, we can use the experiences from the making of the terminology and nomenclature system of Earth undersea topography. [1] The nomenclature system and the terminology used by astrogeologists could be revised. Common names of features should be defined (nova, tessera, volcano, tholus, lobate ejecta crater etc) with a type example for each. A well defined hierarchy for landscape types should be defined. The Moon is the best example, since it uses many names that originates from the 17th century, mixed

  6. Introducing native landscape ecology to Hanford cleanup

    SciTech Connect

    Jim, R.; Nguyen, G.; Barry, B.

    1995-12-31

    Responsible management of environmental and public health risk requires a fundamental understanding of the intra-, inter-, and integral components of the hierarchical interaction dynamics within a pollution affected ecosystem. Because the ecosphere is a heterogeneous combination of many subecosystems of plant and animal species, its component interactions sustaining the complex whole are spatially mediated, and such an adaptive self-stabilizing ecomosaic often possesses long disintegration and regeneration times for the manifestation of observable consequences, quantitative assessment of its future structural and functional changes can be deceptive or plagued with irreducible uncertainty. This paper presents an holistic framework for the direct integration of native traditional environmental knowledge with the landscape ecology information system to refine and actualize the understanding of acceptable long-range risk and its collective estimation for an endangered population or community. An illustrative application of riparian zone restoration in the Hanford reach for wild salmon runs and habitat preservation is also discussed.

  7. Spatiotemporal microbial evolution on antibiotic landscapes.

    PubMed

    Baym, Michael; Lieberman, Tami D; Kelsic, Eric D; Chait, Remy; Gross, Rotem; Yelin, Idan; Kishony, Roy

    2016-09-09

    A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front. While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front, we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behind more sensitive lineages. The MEGA-plate provides a versatile platform for studying microbial adaption and directly visualizing evolutionary dynamics.

  8. Landscapes of the Digital Baroque.

    PubMed

    Singh, Gary

    2016-01-01

    Alvaro Ocampo traversed many landscapes to arrive at his current space in the digital art landscape. Eventually, the artist then made his way to the digital world, where he is no longer subjected to the tyranny of the one-off. He believes digital art is the new version of traditional etching in the way that it eliminates the idea of the one original piece of art.

  9. Protein evolution on rugged landscapes.

    PubMed Central

    Macken, C A; Perelson, A S

    1989-01-01

    We analyze a mathematical model of protein evolution in which the evolutionary process is viewed as hill-climbing on a random fitness landscape. In studying the structure of such landscapes, we note that a large number of local optima exist, and we calculate the time and number of mutational changes until a protein gets trapped at a local optimum. Such a hill-climbing process may underlie the evolution of antibody molecules by somatic hypermutation. PMID:2762321

  10. Landscape evolution by soil redistribution in a Mediterranean agricultural context

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Follain, Stéphane; Le Bissonnais, Yves

    2010-05-01

    climate changes on soil cover and landscape evolution. The model has been tested on a watershed unit (91 ha) located at Roujan (43°30'N - 3°19'E) in the south of France (Hérault, France). Its first justification is to allow the study of global changes affecting hydrosystems in agro-systems located in Mediterranean context. Mediterranean environment is well adapted to study the system vulnerability to anthropic and climatic pressure changes. The pedological dataset is based on the soils map (1/25 000) of the watershed established by Coulouma et al. (2008) refined with data collected during two pedological surveys implementing a 25 m square sampling scheme for soil description. The simulated soil depth evolution, compared to the present soil cover detailed by the surveying, seems to confirm the observed patterns in terms of soil redistribution and topographic evolution. Land use, cultural practices and agricultural landscape structure are also able to directly influence sediment fluxes, then the related landscape evolution. The present landscape structure, tested under the perspective of climate changing showed a mitigating effect in terms of soil erosion confirming the importance of a detailed representation of the system geometry in modelling practises.

  11. Titan Polar Landscape Evolution

    NASA Technical Reports Server (NTRS)

    Moore, Jeffrey M.

    2016-01-01

    With the ongoing Cassini-era observations and studies of Titan it is clear that the intensity and distribution of surface processes (particularly fluvial erosion by methane and Aeolian transport) has changed through time. Currently however, alternate hypotheses substantially differ among specific scenarios with respect to the effects of atmospheric evolution, seasonal changes, and endogenic processes. We have studied the evolution of Titan's polar region through a combination of analysis of imaging, elevation data, and geomorphic mapping, spatially explicit simulations of landform evolution, and quantitative comparison of the simulated landscapes with corresponding Titan morphology. We have quantitatively evaluated alternate scenarios for the landform evolution of Titan's polar terrain. The investigations have been guided by recent geomorphic mapping and topographic characterization of the polar regions that are used to frame hypotheses of process interactions, which have been evaluated using simulation modeling. Topographic information about Titan's polar region is be based on SAR-Topography and altimetry archived on PDS, SAR-based stereo radar-grammetry, radar-sounding lake depth measurements, and superposition relationships between geomorphologic map units, which we will use to create a generalized topographic map.

  12. PSEUDO-CODEWORD LANDSCAPE

    SciTech Connect

    CHERTKOV, MICHAEL; STEPANOV, MIKHAIL

    2007-01-10

    The authors discuss performance of Low-Density-Parity-Check (LDPC) codes decoded by Linear Programming (LP) decoding at moderate and large Signal-to-Noise-Ratios (SNR). Frame-Error-Rate (FER) dependence on SNR and the noise space landscape of the coding/decoding scheme are analyzed by a combination of the previously introduced instanton/pseudo-codeword-search method and a new 'dendro' trick. To reduce complexity of the LP decoding for a code with high-degree checks, {ge} 5, they introduce its dendro-LDPC counterpart, that is the code performing identifically to the original one under Maximum-A-Posteriori (MAP) decoding but having reduced (down to three) check connectivity degree. Analyzing number of popular LDPC codes and their dendro versions performing over the Additive-White-Gaussian-Noise (AWGN) channel, they observed two qualitatively different regimes: (i) error-floor sets early, at relatively low SNR, and (ii) FER decays with SNR increase faster at moderate SNR than at the largest SNR. They explain these regimes in terms of the pseudo-codeword spectra of the codes.

  13. Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

    EPA Science Inventory

    Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

  14. Landscape Visualisation on the Internet

    NASA Astrophysics Data System (ADS)

    Imhof, M. P.; Cox, M. T.; Harvey, D. W.; Heemskerk, G. E.; Pettit, C. J.

    2012-07-01

    The Victorian Resources Online (VRO) website (http://www.dpi.vic.gov.au/vro) is the principal means for accessing landscapebased information in Victoria. In this paper we introduce a range of online landscape visualisations that have been developed to enhance existing static web content around the nature and distribution of Victoria's landforms and soils as well as associated processes. Flash is used to develop online visualisations that include interactive landscape panoramas, animations of soil and landscape processes and videos of experts explaining features in the field as well as landscape "flyovers". The use of interactive visualisations adds rich information multimedia content to otherwise static pages and offers the potential to improve user's appreciation and understanding of soil and landscapes. Visualisation is becoming a key component of knowledge management activities associated with VRO - proving useful for both "knowledge capture" (from subject matter specialists) and "knowledge transfer" to a diverse user base. A range of useful visualisation products have been made available online, with varying degrees of interactivity and suited to a variety of users. The use of video files, animation and interactive visualisations is adding rich information content to otherwise static web pages. These information products offer new possibilities to enhance learning of landscapes and the effectiveness of these will be tested as the next phase of development.

  15. Hiking Over Quantum Control Landscapes

    NASA Astrophysics Data System (ADS)

    Rabitz, Herschel

    2008-03-01

    Seeking the best control over a posed quantum dynamic objective entails climbing over the associated control landscape, which is defined as the quantum mechanical observable as a function of the controls. The topology and general structure of quantum control landscapes as input output maps dictate the final attainable yield, the efficiency of the search for an effective control, the possible existence of multiple dynamically equivalent controls, and the robustness of any viable control solution. Normal optimization problems in virtually any area of engineering and science typically have landscape topologies that remain a mystery. Quantum mechanics appears out to be quite special in that the topology of quantum control landscapes can be established generically based on minimal physical assumptions. Various features of these landscapes will be discussed and illustrated for circumstances where the controls are either an external field or the time independent portions of the Hamiltonian; the latter circumstance corresponds to subjecting the material or molecules to systematic variation and hence viewed in the context of being controls. Both theoretical and experimental findings on control landscapes and their consequences will be discussed, including issues of robustness to noise, search algorithm efficiency, existence of multiple control solutions, prospects for identifying reduced sets of control variables, simultaneous control of multiple quantum systems (optimal dynamic discrimination (ODD)), and mechanism analysis.

  16. Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape

    NASA Astrophysics Data System (ADS)

    Schwartz, N.; Uriarte, M.; DeFries, R. S.; Gutierrez-Velez, V. H.; Fernandes, K.; Pinedo-Vasquez, M.

    2015-12-01

    Wind is a major disturbance in the Amazon and has both short-term impacts and lasting legacies in tropical forests. Observed patterns of damage across landscapes result from differences in wind exposure and stand characteristics, such as tree stature, species traits, successional age, and fragmentation. Wind disturbance has important consequences for biomass dynamics in Amazonian forests, and understanding the spatial distribution and size of impacts is necessary to quantify the effects on carbon dynamics. In November 2013, a mesoscale convective system was observed over the study area in Ucayali, Peru, a highly human modified and fragmented forest landscape. We mapped downfall damage associated with the storm in order to ask: how does the severity of damage vary within forest patches, and across forest patches of different sizes and successional ages? We applied spectral mixture analysis to Landsat images from 2013 and 2014 to calculate the change in non-photosynthetic vegetation fraction after the storm, and combined it with C-band SAR data from the Sentinel-1 satellite to predict downfall damage measured in 30 field plots using random forest regression. We then applied this model to map damage in forests across the study area. Using a land cover classification developed in a previous study, we mapped secondary and mature forest, and compared the severity of damage in the two. We found that damage was on average higher in secondary forests, but patterns varied spatially. This study demonstrates the utility of using multiple sources of satellite data for mapping wind disturbance, and adds to our understanding of the sources of variation in wind-related damage. Ultimately, an improved ability to map wind impacts and a better understanding of their spatial patterns can contribute to better quantification of carbon dynamics in Amazonian landscapes.

  17. Landscape structure affects specialists but not generalists in naturally fragmented grasslands.

    PubMed

    Miller, Jesse E D; Damschen, Ellen I; Harrison, Susan P; Grace, James B

    2015-12-01

    Understanding how biotic communities respond to landscape spatial structure is critically important for conservation management as natural habitats become increasingly fragmented. However, empirical studies of the effects of spatial structure on plant species richness have found inconsistent results, suggesting that more comprehensive approaches are needed. We asked how landscape structure affects total plant species richness and the richness of a guild of specialized plants in a multivariate context. We sampled herbaceous plant communities at 56 dolomite glades (insular, fire-adapted grasslands) across the Missouri Ozarks, USA, and used structural equation modeling (SEM) to analyze the relative importance of landscape structure, soil resource availability, and fire history for plant communities. We found that landscape spatial structure, defined as the area-weighted proximity of glade habitat surrounding study sites (proximity index), had a significant effect on total plant species richness, but only after we controlled for environmental covariates. Richness of specialist species, but not generalists, was positively related to landscape spatial structure. Our results highlight that local environmental filters must be considered to understand the influence of landscape structure on communities and that unique species guilds may respond differently to landscape structure than the community as a whole. These findings suggest that both local environment and landscape context should be considered when developing management strategies for species of conservation concern in fragmented habitats.

  18. Landscape and climate science and scenarios for Florida

    USGS Publications Warehouse

    Terando, Adam; Traxler, Steve; Collazo, Jaime

    2014-01-01

    The Peninsular Florida Landscape Conservation Cooperative (PFLCC) is part of a network of 22 Landscape Conservation Cooperatives (LCCs) that extend from Alaska to the Caribbean. LCCs are regional-applied conservation-science partnerships among Federal agencies, regional organizations, States, tribes, nongovernmental organizations (NGOs), private stakeholders, universities, and other entities within a geographic area. The goal of these conservation-science partnerships is to help inform managers and decision makers at a landscape scale to further the principles of adaptive management and strategic habitat conservation. A major focus for LCCs is to help conservation managers and decision makers respond to large-scale ecosystem and habitat stressors, such as climate change, habitat fragmentation, invasive species, and water scarcity. The purpose of the PFLCC is to facilitate planning, design, and implementation of conservation strategies for fish and wildlife species at the landscape level using the adaptive management framework of strategic habitat conservation—integrating planning, design, delivery, and evaluation. Florida faces a set of unique challenges when responding to regional and global stressors because of its unique ecosystems and assemblages of species, its geographic location at the crossroads of temperate and tropical climates, and its exposure to both rapid urbanization and rising sea levels as the climate warms. In response to these challenges, several landscape-scale science projects were initiated with the goal of informing decision makers about how potential changes in climate and the built environment could impact habitats and ecosystems of concern in Florida and the Southeast United States. In June 2012, the PFLCC, North Carolina State University, convened a workshop at the U.S. Geological Survey (USGS) Coastal and Marine Science Center in St. Petersburg to assess the results of these integrated assessments and to foster an open dialogue about

  19. Visual Adaptation

    PubMed Central

    Webster, Michael A.

    2015-01-01

    Sensory systems continuously mold themselves to the widely varying contexts in which they must operate. Studies of these adaptations have played a long and central role in vision science. In part this is because the specific adaptations remain a powerful tool for dissecting vision, by exposing the mechanisms that are adapting. That is, “if it adapts, it's there.” Many insights about vision have come from using adaptation in this way, as a method. A second important trend has been the realization that the processes of adaptation are themselves essential to how vision works, and thus are likely to operate at all levels. That is, “if it's there, it adapts.” This has focused interest on the mechanisms of adaptation as the target rather than the probe. Together both approaches have led to an emerging insight of adaptation as a fundamental and ubiquitous coding strategy impacting all aspects of how we see. PMID:26858985

  20. Efficient escape from local optima in a highly rugged fitness landscape by evolving RNA virus populations.

    PubMed

    Cervera, Héctor; Lalić, Jasna; Elena, Santiago F

    2016-08-17

    Predicting viral evolution has proven to be a particularly difficult task, mainly owing to our incomplete knowledge of some of the fundamental principles that drive it. Recently, valuable information has been provided about mutation and recombination rates, the role of genetic drift and the distribution of mutational, epistatic and pleiotropic fitness effects. However, information about the topography of virus' adaptive landscapes is still scarce, and to our knowledge no data has been reported so far on how its ruggedness may condition virus' evolvability. Here, we show that populations of an RNA virus move efficiently on a rugged landscape and scape from the basin of attraction of a local optimum. We have evolved a set of Tobacco etch virus genotypes located at increasing distances from a local adaptive optimum in a highly rugged fitness landscape, and we observed that few evolved lineages remained trapped in the local optimum, while many others explored distant regions of the landscape. Most of the diversification in fitness among the evolved lineages was explained by adaptation, while historical contingency and chance events contribution was less important. Our results demonstrate that the ruggedness of adaptive landscapes is not an impediment for RNA viruses to efficiently explore remote parts of it.

  1. Remotely-Sensed Urban Wet-Landscapes AN Indicator of Coupled Effects of Human Impact and Climate Change

    NASA Astrophysics Data System (ADS)

    Ji, Wei

    2016-06-01

    This study proposes the concept of urban wet-landscapes (loosely-defined wetlands) as against dry-landscapes (mainly impervious surfaces). The study is to examine whether the dynamics of urban wet-landscapes is a sensitive indicator of the coupled effects of the two major driving forces of urban landscape change - human built-up impact and climate (precipitation) variation. Using a series of satellite images, the study was conducted in the Kansas City metropolitan area of the United States. A rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. The spatial analyses of wetland changes were implemented at the scales of metropolitan, watershed, and sub-watershed as well as based on the size of surface water bodies in order to reveal urban wetland change trends in relation to the driving forces. The study identified that wet-landscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while smaller wetlands decreased mainly due to human development activities. These findings suggest that wet-landscapes, as against the dry-landscapes, can be a more effective indicator of the coupled effects of human impact and climate change.

  2. [Dynamic changes of landscape pattern and eco-disturbance degree in Shuangtai estuary wetland of Liaoning Province, China].

    PubMed

    Chen, Ai-lian; Zhu, Bo-qin; Chen, Li-ding; Wu, Yan-hua; Sun, Ran-hao

    2010-05-01

    The main objective of establishing natural reserve is to protect its natural resources from human disturbances and maintain its critical ecological service values. This paper introduced the concept of hemeroby, and by using remote sensing technology, systematically assessed the dynamic changes of landscape pattern and eco-disturbance degree in Shuangtai estuary wetland of Liaoning Province, China. Firstly, a knowledge-based expert system was used to classify the landscape into three first-level types based on eco-disturbance degree, i.e., undisturbed, partially disturbed, or completely disturbed, which were further classified into 30 second-level categories. Secondly, questionnaire and experts knowledge were adopted to determine the hemeroby index for each landscape type and to formulate a landscape classification system. Finally, the landscape classification maps and hemeroby indices were derived by using the Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) data acquired on 30 April 1987, 7 June 1995, 12 June 2000, and 11 October 2006. The results indicated that from 1987 to 2006, the landscape patches in the study area became more fragmented, being most obvious for reed marsh. Undisturbed landscape type decreased in area, while partially and completely disturbed types were in adverse. The overall characteristics of the spatial distribution of hemeroby index were of most variable in the areas along the river and surrounding the estuary and being the highest in the areas surrounding the city, largely due to the rapid urbanization and the blooming fishery in the study area.

  3. Adaptive genetic variation and population differences

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Humans are physiologically and morphologically diverse. Such diversities have been shaped by demographic history and adaptation to local environments, including regional climate, landscape, food source, culture, and pathogens since their expansion within and out of Africa between 50,000 and 100,000 ...

  4. Neighbourhood-scale urban forest ecosystem classification.

    PubMed

    Steenberg, James W N; Millward, Andrew A; Duinker, Peter N; Nowak, David J; Robinson, Pamela J

    2015-11-01

    Urban forests are now recognized as essential components of sustainable cities, but there remains uncertainty concerning how to stratify and classify urban landscapes into units of ecological significance at spatial scales appropriate for management. Ecosystem classification is an approach that entails quantifying the social and ecological processes that shape ecosystem conditions into logical and relatively homogeneous management units, making the potential for ecosystem-based decision support available to urban planners. The purpose of this study is to develop and propose a framework for urban forest ecosystem classification (UFEC). The multifactor framework integrates 12 ecosystem components that characterize the biophysical landscape, built environment, and human population. This framework is then applied at the neighbourhood scale in Toronto, Canada, using hierarchical cluster analysis. The analysis used 27 spatially-explicit variables to quantify the ecosystem components in Toronto. Twelve ecosystem classes were identified in this UFEC application. Across the ecosystem classes, tree canopy cover was positively related to economic wealth, especially income. However, education levels and homeownership were occasionally inconsistent with the expected positive relationship with canopy cover. Open green space and stocking had variable relationships with economic wealth and were more closely related to population density, building intensity, and land use. The UFEC can provide ecosystem-based information for greening initiatives, tree planting, and the maintenance of the existing canopy. Moreover, its use has the potential to inform the prioritization of limited municipal resources according to ecological conditions and to concerns of social equity in the access to nature and distribution of ecosystem service supply.

  5. Genomic landscape of liposarcoma

    PubMed Central

    Kanojia, Deepika; Nagata, Yasunobu; Garg, Manoj; Lee, Dhong Hyun; Sato, Aiko; Yoshida, Kenichi; Sato, Yusuke; Sanada, Masashi; Mayakonda, Anand; Bartenhagen, Christoph; Klein, Hans-Ulrich; Doan, Ngan B.; Said, Jonathan W.; Mohith, S.; Gunasekar, Swetha; Shiraishi, Yuichi; Chiba, Kenichi; Tanaka, Hiroko; Miyano, Satoru; Myklebost, Ola; Yang, Henry; Dugas, Martin; Meza-Zepeda, Leonardo A.; Silberman, Allan W.; Forscher, Charles; Tyner, Jeffrey W.; Ogawa, Seishi; Koeffler, H. Phillip

    2015-01-01

    Liposarcoma (LPS) is the most common type of soft tissue sarcoma accounting for 20% of all adult sarcomas. Due to absence of clinically effective treatment options in inoperable situations and resistance to chemotherapeutics, a critical need exists to identify novel therapeutic targets. We analyzed LPS genomic landscape using SNP arrays, whole exome sequencing and targeted exome sequencing to uncover the genomic information for development of specific anti-cancer targets. SNP array analysis indicated known amplified genes (MDM2, CDK4, HMGA2) and important novel genes (UAP1, MIR557, LAMA4, CPM, IGF2, ERBB3, IGF1R). Carboxypeptidase M (CPM), recurrently amplified gene in well-differentiated/de-differentiated LPS was noted as a putative oncogene involved in the EGFR pathway. Notable deletions were found at chromosome 1p (RUNX3, ARID1A), chromosome 11q (ATM, CHEK1) and chromosome 13q14.2 (MIR15A, MIR16-1). Significantly and recurrently mutated genes (false discovery rate < 0.05) included PLEC (27%), MXRA5 (21%), FAT3 (24%), NF1 (20%), MDC1 (10%), TP53 (7%) and CHEK2 (6%). Further, in vitro and in vivo functional studies provided evidence for the tumor suppressor role for Neurofibromin 1 (NF1) gene in different subtypes of LPS. Pathway analysis of recurrent mutations demonstrated signaling through MAPK, JAK-STAT, Wnt, ErbB, axon guidance, apoptosis, DNA damage repair and cell cycle pathways were involved in liposarcomagenesis. Interestingly, we also found mutational and copy number heterogeneity within a primary LPS tumor signifying the importance of multi-region sequencing for cancer-genome guided therapy. In summary, these findings provide insight into the genomic complexity of LPS and highlight potential druggable pathways for targeted therapeutic approach. PMID:26643872

  6. Using landscape history to predict biodiversity patterns in fragmented landscapes.

    PubMed

    Ewers, Robert M; Didham, Raphael K; Pearse, William D; Lefebvre, Véronique; Rosa, Isabel M D; Carreiras, João M B; Lucas, Richard M; Reuman, Daniel C

    2013-10-01

    Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape 'terrageny', which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes.

  7. Using landscape history to predict biodiversity patterns in fragmented landscapes

    PubMed Central

    Ewers, Robert M; Didham, Raphael K; Pearse, William D; Lefebvre, Véronique; Rosa, Isabel M D; Carreiras, João M B; Lucas, Richard M; Reuman, Daniel C

    2013-01-01

    Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape ‘terrageny’, which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes. PMID:23931035

  8. Managing for Climate Change in Western Forest Ecosystems; The Role of Refugia in Adaptation Strategies (Invited)

    NASA Astrophysics Data System (ADS)

    Millar, C. I.; Morelli, T.

    2009-12-01

    Managing forested ecosystems in western North America for adaptation to climate change involves options that depend on resource objectives, landscape conditions, sensitivity to change, and social desires. Strategies range from preserving species and ecosystems in the face of change (resisting change); managing for resilience to change; realigning ecosystems that have been severely altered so that they can adapt successfully; and enabling species to respond to climate changes. We are exploring one extreme in this range of strategies, that is, to manage locations, species, communities, or ecosystems as refugia. This concept is familiar from the Quaternary literature as isolated locations where climates remained warm during cold glacial intervals and wherein species contracted and persisted in small populations. References to refugia have been made in the climate-adaptation literature but little elaborated, and applications have not been described. We are addressing this gap conceptually and in case-studies from national forest and national park environments in California. Using a classification of refugium categories, we extend the concept beyond the original use to include diverse locations and conditions where plant or animal species, or ecosystems of concern, would persist during future changing climatic backgrounds. These locations may be determined as refugial for reasons of local microclimate, substrate, elevation, topographic context, paleohistory, species ecology, or management capacity. Recognizing that species and ecosystems respond to climate change differently, refugium strategies are appropriate in some situations and not others. We describe favorable conditions for using refugium strategies and elaborate specific approaches in Sierra Nevada case studies.

  9. Exploring constrained quantum control landscapes

    NASA Astrophysics Data System (ADS)

    Moore, Katharine W.; Rabitz, Herschel

    2012-10-01

    The broad success of optimally controlling quantum systems with external fields has been attributed to the favorable topology of the underlying control landscape, where the landscape is the physical observable as a function of the controls. The control landscape can be shown to contain no suboptimal trapping extrema upon satisfaction of reasonable physical assumptions, but this topological analysis does not hold when significant constraints are placed on the control resources. This work employs simulations to explore the topology and features of the control landscape for pure-state population transfer with a constrained class of control fields. The fields are parameterized in terms of a set of uniformly spaced spectral frequencies, with the associated phases acting as the controls. This restricted family of fields provides a simple illustration for assessing the impact of constraints upon seeking optimal control. Optimization results reveal that the minimum number of phase controls necessary to assure a high yield in the target state has a special dependence on the number of accessible energy levels in the quantum system, revealed from an analysis of the first- and second-order variation of the yield with respect to the controls. When an insufficient number of controls and/or a weak control fluence are employed, trapping extrema and saddle points are observed on the landscape. When the control resources are sufficiently flexible, solutions producing the globally maximal yield are found to form connected "level sets" of continuously variable control fields that preserve the yield. These optimal yield level sets are found to shrink to isolated points on the top of the landscape as the control field fluence is decreased, and further reduction of the fluence turns these points into suboptimal trapping extrema on the landscape. Although constrained control fields can come in many forms beyond the cases explored here, the behavior found in this paper is illustrative of

  10. Security classification of information

    SciTech Connect

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  11. Recursive heuristic classification

    NASA Technical Reports Server (NTRS)

    Wilkins, David C.

    1994-01-01

    The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

  12. Adaptive Management

    EPA Science Inventory

    Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive managem...

  13. The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

    USGS Publications Warehouse

    Ramsey, Elijah W.; Nelson, G.A.; Echols, D.; Sapkota, S.K.

    2002-01-01

    The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

  14. Hidden Randomness between Fitness Landscapes Limits Reverse Evolution

    NASA Astrophysics Data System (ADS)

    Tan, Longzhi; Serene, Stephen; Xiao Chao, Hui; Gore, Jeff

    2012-02-01

    Natural populations must constantly adapt to the ever-changing environment. A fundamental question in evolutionary biology is whether adaptations can be reversed by returning the population to its ancestral environment. Traditionally, reverse evolution is defined as restoring an ancestral phenotype (physical characteristics such as body size), and the classic Dollo's Law has hypothesized the impossibility of reversing complex adaptations. However, this ``law'' remains ambiguous unless reverse evolution can be studied at the level of genotypes (the underlying genome sequence). We measured the fitness landscapes of a bacterial antibiotic-resistance gene and analyzed the reversibility of evolution as a global, statistical feature of the landscapes. In both experiments and simulations, we find that an adaptation's reversibility declines as the number of mutations it involves increases, suggesting a probabilistic form of Dollo's Law at the molecular level. We also show computationally that slowly switching between environments facilitates reverse evolution in small populations, where clonal interference is negligible or moderate. This is an analogy to thermodynamics, where the reversibility of a physical process is maximized when conditions are modified infinitely slowly.

  15. Classification of Stellar Spectra

    NASA Astrophysics Data System (ADS)

    Garrison, R.; Murdin, P.

    2000-11-01

    How does a scientist approach the problem of trying to understand countless billions of objects? One of the first steps is to organize the data and set up a classification scheme which can provide the best insights into the nature of the objects. Perception and insight are the main purposes of classification. In astronomy, where there are `billions and billions' of stars, classification is an ong...

  16. Classiology and soil classification

    NASA Astrophysics Data System (ADS)

    Rozhkov, V. A.

    2012-03-01

    Classiology can be defined as a science studying the principles and rules of classification of objects of any nature. The development of the theory of classification and the particular methods for classifying objects are the main challenges of classiology; to a certain extent, they are close to the challenges of pattern recognition. The methodology of classiology integrates a wide range of methods and approaches: from expert judgment to formal logic, multivariate statistics, and informatics. Soil classification assumes generalization of available data and practical experience, formalization of our notions about soils, and their representation in the form of an information system. As an information system, soil classification is designed to predict the maximum number of a soil's properties from the position of this soil in the classification space. The existing soil classification systems do not completely satisfy the principles of classiology. The violation of logical basis, poor structuring, low integrity, and inadequate level of formalization make these systems verbal schemes rather than classification systems sensu stricto. The concept of classification as listing (enumeration) of objects makes it possible to introduce the notion of the information base of classification. For soil objects, this is the database of soil indices (properties) that might be applied for generating target-oriented soil classification system. Mathematical methods enlarge the prognostic capacity of classification systems; they can be applied to assess the quality of these systems and to recognize new soil objects to be included in the existing systems. The application of particular principles and rules of classiology for soil classification purposes is discussed in this paper.

  17. The complex landscape of pancreatic cancer metabolism

    PubMed Central

    Sousa, Cristovão Marques; Kimmelman, Alec C.

    2014-01-01

    Pancreatic ductal adenocarcinomas (PDA) are extremely aggressive cancers and currently available therapies are only minimally effective in treating this disease. Tackling this devastating cancer has been a major challenge to the scientific and medical communities, in part due to its intense therapeutic resistance. One of the aspects of this tumor that contributes to its aggressive behavior is its altered cellular metabolism. Indeed, PDA cells seem to possess the ability to adapt their metabolism to the particular environment to which they are exposed, including utilizing diverse fuel sources depending on their availability. Moreover, PDA tumors are efficient at recycling various metabolic substrates through activation of different salvage pathways such as autophagy and macropinocytosis. Together, these diverse metabolic adaptations allow PDA cells to survive and thrive in harsh environments that may lack nutrients and oxygen. Not surprisingly, given its central role in the pathogenesis of this tumor, oncogenic Kras plays a critical role in much of the metabolic reprogramming seen in PDA. In this review, we discuss the metabolic landscape of PDA tumors, including the molecular underpinnings of the key regulatory nodes, and describe how such pathways can be exploited for future diagnostic and therapeutic approaches PMID:24743516

  18. Geotechnology and landscape ecology applied to the selection of potential forest fragments for seed harvesting.

    PubMed

    Santos, Alexandre Rosa Dos; Antonio Alvares Soares Ribeiro, Carlos; de Oliveira Peluzio, Telma Machado; Esteves Peluzio, João Batista; de Queiroz, Vagner Tebaldi; Figueira Branco, Elvis Ricardo; Lorenzon, Alexandre Simões; Domingues, Getulio Fonseca; Marcatti, Gustavo Eduardo; de Castro, Nero Lemos Martins; Teixeira, Thaisa Ribeiro; Dos Santos, Gleissy Mary Amaral Dino Alves; Santos Mota, Pedro Henrique; Ferreira da Silva, Samuel; Vargas, Rozimelia; de Carvalho, José Romário; Macedo, Leandro Levate; da Silva Araújo, Cintia; de Almeida, Samira Luns Hatum

    2016-12-01

    The Atlantic Forest biome is recognized for its biodiversity and is one of the most threatened biomes on the planet, with forest fragmentation increasing due to uncontrolled land use, land occupation, and population growth. The most serious aspect of the forest fragmentation process is the edge effect and the loss of biodiversity. In this context, the aim of this study was to evaluate the dynamics of forest fragmentation and select potential forest fragments with a higher degree of conservation for seed harvesting in the Itapemirim river basin, Espírito Santo State, Brazil. Image classification techniques, forest landscape ecology, and multi-criteria analysis were used to evaluate the evolution of forest fragmentation to develop the landscape metric indexes, and to select potential forest fragments for seed harvesting for the years 1985 and 2013. According to the results, there was a reduction of 2.55% of the occupancy of the fragments in the basin between the years 1985 and 2013. For the years 1985 and 2013, forest fragment units 2 and 3 were spatialized with a high potential for seed harvesting, representing 6.99% and 16.01% of the total fragments, respectively. The methodology used in this study has the potential to be used to support decisions for the selection of potential fragments for seed harvesting because selecting fragments in different environments by their spatial attributes provides a greater degree of conservation, contributing to the protection and conscious management of the forests. The proposed methodology can be adapted to other areas and different biomes of the world.

  19. [Selection of landscape metrics for urban forest based on simulated landscapes].

    PubMed

    Liu, Chang-Fu; Li, Jing-Ze; Li, Xiao-Ma; He, Xing-Yuan; Chen, Wei

    2009-05-01

    Based on the existing urban forest landscape of Shenyang, four landscape pattern gradients were simulated, and one existing landscape pattern gradient in accordance with the trend of these gradients was selected. By analyzing the responses of 28 landscape metrics for landscape fragmentation and patch shape complexity to various landscape pattern gradients, preference landscape metrics were selected for describing the degree of the two landscape pattern characteristics. The results showed that patch density (PD) and mean patch area (AREA_MN) regularly responded to the change of landscape fragmentation. The increase of landscape fragmentation resulted in an increase of PD value while a decrease of AREA_MN value. Patch shape complexity of area weighted mean perimeter area ratio (PARA_AM) coincided with the gradients of landscape pattern. PARA AM value increased with increasing patch shape complexity, which precisely characterized the degree of patch shape complexity.

  20. Analysis of uncertainty in multi-temporal object-based classification

    NASA Astrophysics Data System (ADS)

    Löw, Fabian; Knöfel, Patrick; Conrad, Christopher

    2015-07-01

    Agricultural management increasingly uses crop maps based on classification of remotely sensed data. However, classification errors can translate to errors in model outputs, for instance agricultural production monitoring (yield, water demand) or crop acreage calculation. Hence, knowledge on the spatial variability of the classier performance is important information for the user. But this is not provided by traditional assessments of accuracy, which are based on the confusion matrix. In this study, classification uncertainty was analyzed, based on the support vector machines (SVM) algorithm. SVM was applied to multi-spectral time series data of RapidEye from different agricultural landscapes and years. Entropy was calculated as a measure of classification uncertainty, based on the per-object class membership estimations from the SVM algorithm. Permuting all possible combinations of available images allowed investigating the impact of the image acquisition frequency and timing, respectively, on the classification uncertainty. Results show that multi-temporal datasets decrease classification uncertainty for different crops compared to single data sets, but there was no "one-image-combination-fits-all" solution. The number and acquisition timing of the images, for which a decrease in uncertainty could be realized, proved to be specific to a given landscape, and for each crop they differed across different landscapes. For some crops, an increase of uncertainty was observed when increasing the quantity of images, even if classification accuracy was improved. Random forest regression was employed to investigate the impact of different explanatory variables on the observed spatial pattern of classification uncertainty. It was strongly influenced by factors related with the agricultural management and training sample density. Lower uncertainties were revealed for fields close to rivers or irrigation canals. This study demonstrates that classification uncertainty estimates

  1. LORICA - A new model for linking landscape and soil profile evolution: Development and sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Temme, Arnaud J. A. M.; Vanwalleghem, Tom

    2016-05-01

    Soils and landscapes evolve in tandem. Landscape position is a strong determinant of vertical soil development, which has often been formalized in the catena concept. At the same time, soil properties are strong determinants of geomorphic processes such as overland erosion, landsliding and creep. We present a new soilscape evolution model; LORICA, to study these numerous interactions between soil and landscape development. The model is based on the existing landscape evolution model LAPSUS and the soil formation model MILESD. The model includes similar soil formation processes as MILESD, but the main novelties include the consideration of more layers and the dynamic adaption of the number of layers as a function of the soil profile's heterogeneity. New processes in the landscape evolution component include a negative feedback of vegetation and armouring and particle size selectivity of the erosion-deposition process. In order to quantify these different interactions, we present a full sensitivity analysis of the input parameters. First results show that the model successfully simulates various soil-landscape interactions, leading to outputs where the surface changes in the landscape clearly depend on soil development, and soil changes depend on landscape location. Sensitivity analysis of the model confirms that soil and landscape interact: variables controlling amount and position of fine clay have the largest effect on erosion, and erosion variables control among others the amount of chemical weathering. These results show the importance of particle size distribution, and especially processes controlling the presence of finer clay particles that are easily eroded, both for the resulting landscape form as for the resulting soil profiles. Further research will have to show whether this is specific to the boundary conditions of this study or a general phenomenon.

  2. Classification criteria for rheumatoid arthritis.

    PubMed

    MacGregor, A J

    1995-05-01

    The development of classification schemes for RA in the last 40 years has followed the increasingly precise understanding of the nature of the clinical disease and the recognition of the different requirements of classification methods in clinic and population settings. In published studies of RA in clinic patients the most widely used criteria sets have been the 1958 ARA (ACR) criteria and its 1961 adaptation (the Rome (active) criteria). These sets classified disease as 'classical', 'definite', 'probable' and 'possible' RA based on criteria comprising clinical, serological, radiological and histological features (the latter were dropped from the Rome criteria set because of their impracticality). More recently, a new criteria set (the 1987 ARA criteria) has been developed using statistical techniques. This set was derived using RA cases and controls attending hospital clinics. It is based on the earlier criteria sets but accommodates the characteristic pattern of joint involvement in RA more precisely. The criteria recognize only the single disease category of 'rheumatoid arthritis'. In validation studies, the 1987 criteria set has been found to have enhanced specificity over earlier schemes in clinic-based studies of RA. The sensitivity may, however, be reduced, in particular in studies of early disease. The application of classification criteria for case recognition in the population and family studies of RA has proved more problematic. In these settings, there is the additional requirement to recognize individuals with remitted and inactive disease as RA cases. The 1966 New York criteria were developed for this specific purpose, however their format proved cumbersome and they have not been widely adopted. The 1987 criteria set is insufficiently sensitive to recognize inactive disease if the criteria are applied exactly as they have been defined. The sensitivity of the 1987 criteria set is, however, substantially enhanced if the criteria are adapted to

  3. HEp-2 Cell Image Classification with Deep Convolutional Neural Networks.

    PubMed

    Gao, Zhimin; Wang, Lei; Zhou, Luping; Zhang, Jianjia

    2016-02-08

    Efficient Human Epithelial-2 (HEp-2) cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which have recently attracted intensive attention in visual recognition. In addition to describing the proposed classification framework, this paper elaborates several interesting observations and findings obtained by our investigation. They include the important factors that impact network design and training, the role of rotation-based data augmentation for cell images, the effectiveness of cell image masks for classification, and the adaptability of the CNN-based classification system across different datasets. Extensive experimental study is conducted to verify the above findings and compares the proposed framework with the well-established image classification models in the literature. The results on benchmark datasets demonstrate that i) the proposed framework can effectively outperform existing models by properly applying data augmentation; ii) our CNN-based framework has excellent adaptability across different datasets, which is highly desirable for cell image classification under varying laboratory settings. Our system is ranked high in the cell image classification competition hosted by ICPR 2014.

  4. Energy Landscape of Social Balance

    NASA Astrophysics Data System (ADS)

    Marvel, Seth A.; Strogatz, Steven H.; Kleinberg, Jon M.

    2009-11-01

    We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social “balance” allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.

  5. Correlates of vernal pool occurrence in the Massachusetts USA, landscape

    USGS Publications Warehouse

    Grant, E.H.C.

    2005-01-01

    Vernal pool wetlands are at risk of destruction across the northeast United States, due in part to their diminutive size and short hydroperiods. These characteristics make it difficult to locate vernal pool habitats in the landscape during much of the year, and no efficient method exists for predicting their occurrence. A logistic regression procedure was used to identify large-scale variables that influence the presence of a potential vernal pool, including surficial geology, land use and land cover, soil classification, topography, precipitation, and surficial hydrologic features. The model was validated with locations of field-verified vernal pools. The model demonstrated that the probability of potential vernal pool occurrence is positively related to slope, negatively related to till/bedrock surficial geology, and negatively related to the proportion of cropland, urban/commercial, and high density residential development in the landscape. The relationship between vernal pool occurrence and large-scale variables suggests that these habitats do not occur at random in the landscape, and thus, protection in situ should be considered.

  6. Martian Landscapes in Motion

    NASA Astrophysics Data System (ADS)

    Mattson, Sarah; McEwen, Alfred; Kirk, Randolph; Howington-Kraus, Elpitha; Chojnacki, Matthew; Runyon, Kirby; Cremonese, Gabriele; Re, Cristina

    2014-05-01

    RISE orthorectified image sequences makes it possible to conduct accurate change detection studies of active processes on Mars. Some examples of studies of active landscapes on Mars using HiRISE DTMs and orthoimage sequences include: dune and ripple motion (Bridges et al., 2012, Nature), recurring slope lineae (RSL) (McEwen et al., 2011, Science; McEwen et al., 2013, Nature Geoscience), gully activity (Dundas et al., 2012, Icarus), and polar processes (Hansen et al., 2011, Science; Portyankina et al. 2013, Icarus,). These studies encompass images from multiple Mars years and seasons. Sequences of orthoimages make it possible to generate animated gifs or movies to visualize temporal changes (http://www.uahirise.org/sim/). They can also be brought into geospatial software to quantitatively map and record changes. The ability to monitor the surface of Mars at high spatial resolution with frequent repeat images has opened up our insight into seasonal and interannual changes, further increasing our understanding of Mars as an active planet.

  7. Benefits and Risks Associated with Landscapes

    EPA Pesticide Factsheets

    To fully reap the benefits that lawns and landscapes can provide our urban and suburban communities, these green spaces must be well-maintained. The landscaping initiative helps manage the benefits and risks associated with lawn care.

  8. 40 CFR 247.15 - Landscaping products.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Landscaping products. (a) Hydraulic mulch products containing recovered paper or recovered wood used for hydroseeding and as an over-spray for straw mulch in landscaping, erosion control, and soil reclamation....

  9. 40 CFR 247.15 - Landscaping products.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Landscaping products. (a) Hydraulic mulch products containing recovered paper or recovered wood used for hydroseeding and as an over-spray for straw mulch in landscaping, erosion control, and soil reclamation....

  10. Imaginative Landscapes: This World and Beyond.

    ERIC Educational Resources Information Center

    Moore, John Noell, Ed.

    2001-01-01

    Describes a variety of books that offer fictional and poetic landscapes--five historical novels set in disparate locales, a book set in medieval Denmark, another addressing the landscape of memory, and a novel about a poet-scientist. (SR)

  11. National-level progress on adaptation

    NASA Astrophysics Data System (ADS)

    Lesnikowski, Alexandra; Ford, James; Biesbroek, Robbert; Berrang-Ford, Lea; Heymann, S. Jody

    2016-03-01

    It is increasingly evident that adaptation will figure prominently in the post-2015 United Nations climate change agreement. As adaptation obligations under the United Nations Framework Convention on Climate Change evolve, more rigorous approaches to measuring adaptation progress among parties will be critical. In this Letter we elaborate on an emerging area of research referred to as `adaptation tracking’, which has potential to inform development of a global adaptation monitoring framework. We evaluate this potential by presenting evidence on policy change for 41 high-income countries between 2010 and 2014. We examine whether countries that were in early stages of adaptation planning in 2010 are making progress to close adaptation gaps, and how the landscape of adaptation in these countries has evolved. In total we find an 87% increase in reported adaptation policies and measures, and evidence that implementation of concrete adaptation initiatives is growing. Reflecting on the strengths and challenges of this early methodology, we further discuss how adaptation tracking practices could guide development of a robust framework for monitoring global adaptation progress and inform future research on policy change across countries.

  12. Multiple ecosystem services in a working landscape.

    PubMed

    Eastburn, Danny J; O'Geen, Anthony T; Tate, Kenneth W; Roche, Leslie M

    2017-01-01

    Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services-specifically agricultural production, biodiversity and habitat, and soil health-across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments.

  13. Microfluidic Platform Generates Oxygen Landscapes for Localized Hypoxic Activation

    PubMed Central

    Rexius, Megan L.; Mauleon, Gerardo; Malik, Asrar B.; Rehman, Jalees; Eddington, David T.

    2014-01-01

    An open-well microfluidic platform generates an oxygen landscape using gas-perfused networks which diffuse across a membrane. The device enables real-time analysis of cellular and tissue responses to oxygen tension to define how cells adapt to heterogeneous oxygen conditions found in the physiological setting. We demonstrate that localized hypoxic activation of cells elicited specific metabolic and gene responses in human microvascular endothelial cells and bone marrow-derived mesenchymal stem cells. A robust demonstration of the compatibility of the device with standard laboratory techniques demonstrates the wide utility of the method. This platform is ideally suited to study real-time cell responses and cell-cell interactions within physiologically relevant oxygen landscapes. PMID:25315003

  14. Microfluidic platform generates oxygen landscapes for localized hypoxic activation.

    PubMed

    Rexius-Hall, Megan L; Mauleon, Gerardo; Malik, Asrar B; Rehman, Jalees; Eddington, David T

    2014-12-21

    An open-well microfluidic platform generates an oxygen landscape using gas-perfused networks which diffuse across a membrane. The device enables real-time analysis of cellular and tissue responses to oxygen tension to define how cells adapt to heterogeneous oxygen conditions found in the physiological setting. We demonstrate that localized hypoxic activation of cells elicited specific metabolic and gene responses in human microvascular endothelial cells and bone marrow-derived mesenchymal stem cells. A robust demonstration of the compatibility of the device with standard laboratory techniques demonstrates the wide utility of the method. This platform is ideally suited to study real-time cell responses and cell-cell interactions within physiologically relevant oxygen landscapes.

  15. Multilayer Perceptrons for Classification

    DTIC Science & Technology

    1992-03-01

    retention/ separation rates fu, input to force projection models. The second application concerns the classification of Armor Piercing Incendiary (API...Air Force pilot reten- tion/ separation rates for input to force projection models. The second application concerns the classification of Armor...methodologies for predicting pilot retention/ separation rates for input to personnel inventory projection models were e::plored. Specifically, the multilayer

  16. Challenges in prosthesis classification.

    PubMed

    Robertsson, Otto; Mendenhall, Stan; Paxton, Elizabeth W; Inacio, Maria C S; Graves, Stephen

    2011-12-21

    Accurate prosthesis classification is critical for total joint arthroplasty surveillance and assessment of comparative effectiveness. Historically, prosthesis classification was based solely on the names of the prosthesis manufacturers. As a result, prosthesis designs changed without corresponding name changes, and other prostheses' names changed over time without substantial design modifications. As the number of prostheses used in total joint arthroplasty on the market increased, catalog and lot numbers associated with prosthesis descriptions were introduced by manufacturers. Currently, these catalog and lot numbers are not standardized, and there is no consensus on categorization of these numbers into brands or subbrands. Classification of the attributes of a prosthesis also varies, limiting comparisons of prostheses across studies and reports. The development of a universal prosthesis classification system would standardize prosthesis classification and enhance total joint arthroplasty research collaboration worldwide. This is a current area of focus for the International Consortium of Orthopaedic Registries (ICOR).

  17. DOE LLW classification rationale

    SciTech Connect

    Flores, A.Y.

    1991-09-16

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission`s classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems.

  18. DOE LLW classification rationale

    SciTech Connect

    Flores, A.Y.

    1991-09-16

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems.

  19. Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

    NASA Astrophysics Data System (ADS)

    Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

    2015-12-01

    Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

  20. Adaptive SPECT

    PubMed Central

    Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.

    2008-01-01

    Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485

  1. Assessing the New Competitive Landscape.

    ERIC Educational Resources Information Center

    Blustain, Harvey; Goldstein, Philip; Lozier, Gregory

    1998-01-01

    Argues that complex forces (new delivery technologies, changing demographics, emergence of corporate universities, global economy) have created a new, competitive landscape for higher education that forces institutions to think methodically about how to respond. A framework for college planning, incorporating three critical components, is…

  2. Flowers and Landscape by Serendipity.

    ERIC Educational Resources Information Center

    Pippin, Sandi

    2003-01-01

    Describes an art lesson in which students sketch drawings of flowers and use watercolor paper and other materials to paint a landscape. Explains that the students also learn about impressionism in this lesson. Discusses how the students prepare the paper and create their artwork. (CMK)

  3. Bioenergy in a Multifunctional Landscape

    SciTech Connect

    Watts, Chad; Negri, Cristina; Ssegane, Herbert

    2015-10-23

    How can our landscapes be managed most effectively to produce crops for food, feed, and bioenergy, while also protecting our water resources by preventing the loss of nutrients from the soil? Dr. Cristina Negri and her team at the U.S. Department of Energy’s Argonne National Laboratory are tackling this question at an agricultural research site located in Fairbury, Illinois.

  4. Selected Landscape Plants. Slide Script.

    ERIC Educational Resources Information Center

    McCann, Kevin

    This slide script, part of a series of slide scripts designed for use in vocational agriculture classes, deals with commercially important woody ornamental landscape plants. Included in the script are narrations for use with a total of 253 slides illustrating 92 different plants. Several slides are used to illustrate each plant: besides a view of…

  5. LANDSCAPING YOUR HOME, TEACHER'S GUIDE.

    ERIC Educational Resources Information Center

    HEDGES, LOWELL E.

    THE PURPOSE OF THIS GUIDE IS TO ASSIST THE VOCATIONAL AGRICULTURE TEACHER TO DEVELOP A UNIT IN THE RELATIVELY SPECIALIZED FIELD OF HOME LANDSCAPING. IT WAS DEVELOPED BY A TEACHER IN CONSULTATION WITH HORTICULTURISTS AND TESTED IN THE CLASSROOM BEFORE PUBLICATION. THE OBJECTIVES OF THE UNIT ARE TO DEVELOP STUDENT ABILITY TO (1) UNDERSTAND THE NEED…

  6. Ornamental Landscape Grasses. Slide Script.

    ERIC Educational Resources Information Center

    Still, Steven M.; Adams, Denise W.

    This slide script to accompany the slide series, Ornamental Landscape Grasses, contains photographs of the 167 slides and accompanying narrative text intended for use in the study and identification of commercially important ornamental grasses and grasslike plants. Narrative text is provided for slides of 62 different perennial and annual species…

  7. Discovery Learning in Landscape Archaeology.

    ERIC Educational Resources Information Center

    O'Brien, Colm; Wheeler, Hazel

    1979-01-01

    A method of discovery learning in which students learn the technique of observing and formulating questions is applied to landscape archaeology. This method demands that the relationship between tutor and student be adjusted so that the tutor becomes a fellow researcher rather than a conveyor of information. (Author/CSS)

  8. The Changing Landscape of Higher Education

    ERIC Educational Resources Information Center

    Staley, David J.; Trinkle, Dennis A.

    2011-01-01

    The landscape of higher education--the growing variety of higher education institutions, the cultural environment, the competitive ecosystem--is changing rapidly and disruptively. The higher education landscape is metaphorically crossed with fault lines, those fissures in the landscape creating potential areas of dramatic change, and is as…

  9. An Analysis of the Landscaping Occupation.

    ERIC Educational Resources Information Center

    Stemple, Lynn L.; Dilley, John E.

    The general purpose of the occupational analysis is to provide workable, basic information dealing with the many and varied duties performed in the landscape services occupation. Depending on the preparation and abilities of the individual student, he may enter the landscape area as (1) nursery worker, (2) landscape planter, (3) landscape…

  10. Weathering instability and landscape evolution

    NASA Astrophysics Data System (ADS)

    Phillips, Jonathan D.

    2005-04-01

    The argument in this paper is that the fundamental control on landscape evolution in erosional landscapes is weathering. The possibility of and evidence for instability in weathering at four scales is examined. The four scales are concerned with weathering processes, allocation of weathered products, the interrelations of weathering and denudation, and the topographic and isostatic responses to weathering-limited denudation (the regolith, hillslope, landscape unit, and landscape scales, respectively). The stability conditions for each model, and the circumstances under which the models themselves are relevant, are used to identify scale-related domains of stability and instability. At the regolith scale, the interactions among weathering rates, resistance, and moisture are unstable, but there are circumstances—over long timescales and where weathering is well advanced—under which the instability is irrelevant. At the hillslope scale, the system is stable when denudation is transport rather than weathering limited and where no renewal of exposure via regolith stripping occurs. At the level of landscape units, the stability model is based entirely on the mutual reinforcements of weathering and erosion. While this should generally lead to instability, the model would be stable where other, external controls of both weathering and erosion rates are stronger than the weathering-erosion feedbacks. At the broadest landscape scale, the inclusion of isostatic responses destabilizes erosion-topography-uplift relationships. Thus, if the spatial or temporal scale is such that isostatic responses are not relevant, the system may be stable. Essentially, instability is prevalent at local spatial scales at all but the longest timescales. Stability at intermediate spatial scales is contingent on whether weathering-erosion feedbacks are strong or weak, with stability being more likely at shorter and less likely at longer timescales. At the broadest spatial scales, instability is

  11. Progress on molecular biomarkers and classification of malignant gliomas.

    PubMed

    Zhang, Chuanbao; Bao, Zhaoshi; Zhang, Wei; Jiang, Tao

    2013-06-01

    Gliomas are the most common primary intracranial tumors in adults. Anaplastic gliomas (WHO grade III) and glioblastomas (WHO grade IV) represent the major groups of malignant gliomas in the brain. Several diagnostic, predictive, and prognostic biomarkers for malignant gliomas have been reported over the last few decades, and these markers have made great contributions to the accuracy of diagnosis, therapeutic decision making, and prognosis of patients. However, heterogeneity in patient outcomes may still be observed, which highlights the insufficiency of a classification system based purely on histopathology. Great efforts have been made to incorporate new information about the molecular landscape of gliomas into novel classifications that may potentially guide treatment. In this review, we summarize three distinctive biomarkers, three most commonly altered pathways, and three classifications based on microarray data in malignant gliomas.

  12. 'Seasons in the Sun’, a colorful new little Bluestem for landscapes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Schizachyrium scoparium, little bluestem, is a warm-season perennial grass native to much of North America. This drought-tolerant plant is tough and adaptable. It is becoming more popular in landscaping due to its low maintenance and attractive foliage, as well as increasing interest in using native...

  13. Characterizing fish community diversity across Virginia landscapes: Prerequisite for conservation

    USGS Publications Warehouse

    Angermeier, P.L.; Winston, M.R.

    1999-01-01

    The number of community types occurring within landscapes is an important, but often unprotected, component of biological diversity. Generally applicable protocols for characterizing community diversity need to be developed to facilitate conservation. We used several multivariate techniques to analyze geographic variation in the composition of fish communities in Virginia streams. We examined relationships between community composition and six landscape variables: drainage basin, physiography, stream order, elevation, channel slope, and map coordinates. We compared patterns at two scales (statewide and subdrainage-specific) to assess sensitivity of community classification to spatial scale. We also compared patterns based on characterizing communities by species composition vs. ecological composition. All landscape variables explained significant proportions of the variance in community composition. Statewide, they explained 32% of the variance in species composition and 48% of the variance in ecological composition. Typical communities in each drainage or physiography were statistically distinctive. Communities in different combinations of drainage, physiography, and stream size were even more distinctive, but composition was strongly spatially autocorrelated. Ecological similarity and species similarity of community pairs were strongly related, but replacement by ecologically similar species was common among drainage-physiography combinations. Landscape variables explained significant proportions of variance in community composition within selected subdrainages, but proportions were less than at the statewide scale, and the explanatory power of individual variables varied considerably among subdrainages. Community variation within subdrainages appeared to be much more closely related to environmental variation than to replacement among ecologically similar species. Our results suggest that taxonomic and ecological characterizations of community composition are

  14. IMPACTS OF PATCH SIZE AND LAND COVER HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

    EPA Science Inventory


    Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of miss-classifying pixels during thematic image classification. However, there has been a lack of empirical evidence to support these hypotheses,...

  15. ASSESSING THE HYDROGEOLOGIC CLASSIFICATION SYSTEM IN MID-ATLANTIC COASTAL PLAIN STREAMS USING BENTHIC MACROINVERTEBRATES

    EPA Science Inventory

    Assessing classification systems that describe natural variation across regions is an important first step for developing indicators. We evaluated a hydrogeologic framework for first order streams in the mid-Atlantic Coastal Plain as part of the LIPS-MACS (Landscape Indicators f...

  16. Geospatial analysis of lake and landscape interactions within the Toolik Lake region, North Slope of Alaska

    NASA Astrophysics Data System (ADS)

    Pathak, Prasad A.

    The Arctic region of Alaska is experiencing severe impacts of climate change. The Arctic lakes ecosystems are bound to undergo alterations in its trophic structure and other chemical properties. However, landscape factors controlling the lake influxes were not studied till date. This research has examined the currently existing lake landscape interactions using Remote Sensing and GIS technology. The statistical modeling was carried out using Regression and CART methods. Remote sensing data was applied to derive the required landscape indices. Remote sensing in the Arctic Alaska faces many challenges including persistent cloud cover, low sun angle and limited snow free period. Tundra vegetation types are interspersed and intricate to classify unlike managed forest stands. Therefore, historical studies have remained underachieved with respect thematic accuracies. However, looking at vegetation communities at watershed level and the implementation of expert classification system achieved the accuracies up to 90%. The research has highlighted the probable role of interactions between vegetation root zones, nutrient availability within active zone, as well as importance of permafrost thawing. Multiple regression analyses and Classification Trees were developed to understand relationships between landscape factors with various chemical parameters as well as chlorophyll readings. Spatial properties of Shrubs and Riparian complexes such as complexity of individual patches at watershed level and within proximity of water channels were influential on Chlorophyll production of lakes. Till-age had significant impact on Total Nitrogen contents. Moreover, relatively young tills exhibited significantly positive correlation with concentration of various ions and conductivity of lakes. Similarly, density of patches of Heath complexes was found to be important with respect to Total Phosphorus contents in lakes. All the regression models developed in this study were significant at 95

  17. Informational landscapes in art, science, and evolution.

    PubMed

    Cohen, Irun R

    2006-07-01

    An informational landscape refers to an array of information related to a particular theme or function. The Internet is an example of an informational landscape designed by humans for purposes of communication. Once it exists, however, any informational landscape may be exploited to serve a new purpose. Listening Post is the name of a dynamic multimedia work of art that exploits the informational landscape of the Internet to produce a visual and auditory environment. Here, I use Listening Post as a prototypic example for considering the creative role of informational landscapes in the processes that beget evolution and science.

  18. Climate adaptation

    NASA Astrophysics Data System (ADS)

    Kinzig, Ann P.

    2015-03-01

    This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.

  19. [Vertical zonation of mountain landscape: a review].

    PubMed

    Sun, Ran-Hao; Chen, Li-Ding; Zhang, Bai-Ping; Fu, Bo-Jie

    2009-07-01

    Vertical gradient of mountain landscape is about 1000 times of its horizontal gradient, and hence, only using landscape pattern index is quite difficult to reflect the landscape regularity along vertical gradient. Mountain altitudinal belt is a kind of classic geographic models representing the vertical differentiation of landscape, being of significance in geographic and ecological researches. However, the discrete expression pattern and the inaccuracy of the borderlines of mountain vertical belts limit the roles of mountain vertical belt in accurately describing landscape pattern in regional scale and in explaining ecological processes. This paper reviewed the research progress and existing problems on mountain altitudinal belt, put forward a suggestion of using modern information technology to establish a comprehensive and continuous mountain landscape information chart, and discussed the framework and prospect of the establishment of the chart, which would have reference value for accurately describing mountain landscape pattern and explaining specific ecological processes, and promote the further improvement of the methodology for mountain ecological research.

  20. Adaptation dynamics of the quasispecies model

    NASA Astrophysics Data System (ADS)

    Jain, Kavita

    2009-02-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  1. Down syndrome and aging: a leadership and social justice landscape.

    PubMed

    Nevel, Kathleen M

    2010-01-01

    The growing phenomenon of aging adults with Down syndrome and other intellectual and developmental disabilities and dementia can be traumatic and overwhelming for families and caregivers. The realization is beset with angst and necessitates restructuring policies and programs while exploring the leadership landscape to facilitate a values framework for persons with Down syndrome. This article considers the changing role of the caregiver and the influences of community support networks, social policy, social justice, and quality of life adaptations for aging persons with Down syndrome and dementia. Note: To maintain confidentiality, personal communications noted throughout this article identify the individual using initials rather than surname.

  2. Landscape-scale modelling of soil carbon dynamics under land use and climate change

    NASA Astrophysics Data System (ADS)

    Lacoste, Marine; Viaud, Valérie; Michot, Didier; Christian, Walter

    2013-04-01

    Soil organic carbon (SOC) sequestration is highly linked to soil use and farming practices, but also to soil redistributions, soil properties, and climate. In a global change context, landscape, farming practice and climate changes are expected; and they will most probably impact SOC dynamics. To assess their respective impacts, we modelled the SOC contents and stocks evolution at the scale of an agricultural landscape, by taking into account the soil redistribution by tillage and water processes. The simulations were conducted from 2010 to 2100 under different scenarios of landscape and climate. These scenarios combined different land uses associated to specific farming practices (mixed dairy with rotations of crops and grasslands, intensive cropping with only crops rotations or permanent grasslands), landscape managements (hedges planting or removal), and climates (business-as-usual climate and climate change, with temperature and precipitations increase). We used a spatially SOC dynamic model (adapted from RothC), coupled to a soil redistribution model (LandSoil). SOC dynamics were spatially modelled with a lateral resolution of 2-m and for soil organic layers up to 105 cm. Initial SOC stocks were described with a 2-m resolution map based on field data and produced with digital soil mapping methods. The major factor of change in SOC stocks was land use change, the second factor of importance was climate change, and finally landscape management: for the total SOC stocks (0-to-105 cm soil layer) the change of land use, climate and landscape management induced a respective mean absolute variation of 10 to 20 tC ha-1, 9 tC ha-1 and 0.4 tC ha-1. When considering the 0-to-105 cm soil layer, the different modelled landscapes showed the same sensitivity to climate change, with induced a mean decrease of 10 tC ha-1. However, the impact of climate change was found different according to the different modelled landscape when considering the 0-to-7.5 and 0-to-30 cm soil

  3. Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

    NASA Astrophysics Data System (ADS)

    Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

    2015-12-01

    Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

  4. Classification of Dartmoor Tors

    DTIC Science & Technology

    1992-09-01

    landscapes: Zeitschrift fir Geomorphologie, Supplement 31, pp 138-160. Brunsden , D ., 1964, The origin of decomposed granite on Dartmoor: IN Dartmoor Essays...edited by I.G. Simmons, Exeter, Devonshire Association for the Advancement of Science, Literature and Art, pp 97-116. Brunsden , D . and Gerrard, J

  5. [Classification of cardiomyopathy].

    PubMed

    Asakura, Masanori; Kitakaze, Masafumi

    2014-01-01

    Cardiomyopathy is a group of cardiovascular diseases with poor prognosis. Some patients with dilated cardiomyopathy need heart transplantations due to severe heart failure. Some patients with hypertrophic cardiomyopathy die unexpectedly due to malignant ventricular arrhythmias. Various phenotypes of cardiomyopathies are due to the heterogeneous group of diseases. The classification of cardiomyopathies is important and indispensable in the clinical situation. However, their classification has not been established, because the causes of cardiomyopathies have not been fully elucidated. We usually use definition and classification offered by WHO/ISFC task force in 1995. Recently, several new definitions and classifications of the cardiomyopathies have been published by American Heart Association, European Society of Cardiology and Japanese Circulation Society.

  6. Delaware Alternative Classifications

    ERIC Educational Resources Information Center

    Miller, Jay

    1975-01-01

    This article discusses the species designation and taxonomies of Delaware and Algonkian and presents eight classifications of taxa by form, habitat, color, movement, sound, use, relationship, and appearance. Relevant research is also reviewed. (CLK)

  7. Postprocessing classification images

    NASA Technical Reports Server (NTRS)

    Kan, E. P.

    1979-01-01

    Program cleans up remote-sensing maps. It can be used with existing image-processing software. Remapped images closely resemble familiar resource information maps and can replace or supplement classification images not postprocessed by this program.

  8. Land Use Classification from Vhr Aerial Images Using Invariant Colour Components and Texture

    NASA Astrophysics Data System (ADS)

    Movia, A.; Beinat, A.; Sandri, T.

    2016-06-01

    Very high resolution (VHR) aerial images can provide detailed analysis about landscape and environment; nowadays, thanks to the rapid growing airborne data acquisition technology an increasing number of high resolution datasets are freely available. In a VHR image the essential information is contained in the red-green-blue colour components (RGB) and in the texture, therefore a preliminary step in image analysis concerns the classification in order to detect pixels having similar characteristics and to group them in distinct classes. Common land use classification approaches use colour at a first stage, followed by texture analysis, particularly for the evaluation of landscape patterns. Unfortunately RGB-based classifications are significantly influenced by image setting, as contrast, saturation, and brightness, and by the presence of shadows in the scene. The classification methods analysed in this work aim to mitigate these effects. The procedures developed considered the use of invariant colour components, image resampling, and the evaluation of a RGB texture parameter for various increasing sizes of a structuring element. To identify the most efficient solution, the classification vectors obtained were then processed by a K-means unsupervised classifier using different metrics, and the results were compared with respect to corresponding user supervised classifications. The experiments performed and discussed in the paper let us evaluate the effective contribution of texture information, and compare the most suitable vector components and metrics for automatic classification of very high resolution RGB aerial images.

  9. A landscape of field theories

    NASA Astrophysics Data System (ADS)

    Maxfield, Travis; Robbins, Daniel; Sethi, Savdeep

    2016-11-01

    Studying a quantum field theory involves a choice of space-time manifold and a choice of background for any global symmetries of the theory. We argue that many more choices are possible when specifying the background. In the context of branes in string theory, the additional data corresponds to a choice of supergravity tensor fluxes. We propose the existence of a landscape of field theory backgrounds, characterized by the space-time metric, global symmetry background and a choice of tensor fluxes. As evidence for this landscape, we study the supersymmetric six-dimensional (2, 0) theory compactified to two dimensions. Different choices of metric and flux give rise to distinct two-dimensional theories, which can preserve differing amounts of supersymmetry.

  10. Reserves, resilience and dynamic landscapes.

    PubMed

    Bengtsson, Janne; Angelstam, Per; Elmqvist, Thomas; Emanuelsson, Urban; Folke, Carl; Ihse, Margareta; Moberg, Fredrik; Nyström, Magnus

    2003-09-01

    In a world increasingly modified by human activities, the conservation of biodiversity is essential as insurance to maintain resilient ecosystems and ensure a sustainable flow of ecosystem goods and services to society. However, existing reserves and national parks are unlikely to incorporate the long-term and large-scale dynamics of ecosystems. Hence, conservation strategies have to actively incorporate the large areas of land that are managed for human use. For ecosystems to reorganize after large-scale natural and human-induced disturbances, spatial resilience in the form of ecological memory is a prerequisite. The ecological memory is composed of the species, interactions and structures that make ecosystem reorganization possible, and its components may be found within disturbed patches as well in the surrounding landscape. Present static reserves should be complemented with dynamic reserves, such as ecological fallows and dynamic successional reserves, that are part of ecosystem management mimicking natural disturbance regimes at the landscape level.

  11. Landscape dynamics of northeastern forests

    NASA Technical Reports Server (NTRS)

    Canham, Charles D.; Silander, John A., Jr.; Civco, Daniel L.

    1994-01-01

    This project involves collaborative research with Stephen W. Pacala and Simon A. Levin of Princeton University to calibrate, test, and analyze models of heterogeneous forested landscapes containing a diverse array of habitats. The project is an extension of previous, NASA-supported research to develop a spatially-explicit model of forest dynamics at the scale of an individual forest stand (hectares to square kilometer spatial scales). That model (SORTIE) has been thoroughly parameterized from field studies in the modal upland environment of western Connecticut. Under our current funding, we are scaling-up the model and parameterizing it for the broad range of upland environments in the region. Our most basic goal is to understand the linkages between stand-level dynamics (as revealed in our previous research) and landscape-level dynamics of forest composition and structure.

  12. Adaptation to elevated CO2 in different biodiversity contexts

    PubMed Central

    Kleynhans, Elizabeth J.; Otto, Sarah P.; Reich, Peter B.; Vellend, Mark

    2016-01-01

    In the absence of migration, species persistence depends on adaption to a changing environment, but whether and how adaptation to global change is altered by community diversity is not understood. Community diversity may prevent, enhance or alter how species adapt to changing conditions by influencing population sizes, genetic diversity and/or the fitness landscape experienced by focal species. We tested the impact of community diversity on adaptation by performing a reciprocal transplant experiment on grasses that evolved for 14 years under ambient and elevated CO2, in communities of low or high species richness. Using biomass as a fitness proxy, we find evidence for local adaptation to elevated CO2, but only for plants assayed in a community of similar diversity to the one experienced during the period of selection. Our results indicate that the biological community shapes the very nature of the fitness landscape within which species evolve in response to elevated CO2. PMID:27510545

  13. Adaptive sleep-wake discrimination for wearable devices.

    PubMed

    Karlen, Walter; Floreano, Dario

    2011-04-01

    Sleep/wake classification systems that rely on physiological signals suffer from intersubject differences that make accurate classification with a single, subject-independent model difficult. To overcome the limitations of intersubject variability, we suggest a novel online adaptation technique that updates the sleep/wake classifier in real time. The objective of the present study was to evaluate the performance of a newly developed adaptive classification algorithm that was embedded on a wearable sleep/wake classification system called SleePic. The algorithm processed ECG and respiratory effort signals for the classification task and applied behavioral measurements (obtained from accelerometer and press-button data) for the automatic adaptation task. When trained as a subject-independent classifier algorithm, the SleePic device was only able to correctly classify 74.94 ± 6.76% of the human-rated sleep/wake data. By using the suggested automatic adaptation method, the mean classification accuracy could be significantly improved to 92.98 ± 3.19%. A subject-independent classifier based on activity data only showed a comparable accuracy of 90.44 ± 3.57%. We demonstrated that subject-independent models used for online sleep-wake classification can successfully be adapted to previously unseen subjects without the intervention of human experts or off-line calibration.

  14. Bioenergy in a Multifunctional Landscape

    ScienceCinema

    Watts, Chad; Negri, Cristina; Ssegane, Herbert

    2016-11-02

    How can our landscapes be managed most effectively to produce crops for food, feed, and bioenergy, while also protecting our water resources by preventing the loss of nutrients from the soil? Dr. Cristina Negri and her team at the U.S. Department of Energy’s Argonne National Laboratory are tackling this question at an agricultural research site located in Fairbury, Illinois.

  15. Sneutrino chaotic inflation and landscape

    NASA Astrophysics Data System (ADS)

    Murayama, Hitoshi; Nakayama, Kazunori; Takahashi, Fuminobu; Yanagida, Tsutomu T.

    2014-11-01

    The most naive interpretation of the BICEP2 data is the chaotic inflation by an inflaton with a quadratic potential. When combined with supersymmetry, we argue that the inflaton plays the role of right-handed scalar neutrino based on rather general considerations. The framework suggests that the right-handed sneutrino tunneled from a false vacuum in a landscape to our vacuum with a small negative curvature and suppressed scalar perturbations at large scales.

  16. Supernova Photometric Lightcurve Classification

    NASA Astrophysics Data System (ADS)

    Zaidi, Tayeb; Narayan, Gautham

    2016-01-01

    This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  17. Vacuum selection on axionic landscapes

    SciTech Connect

    Wang, Gaoyuan; Battefeld, Thorsten E-mail: tbattefe@astro.physik.uni-goettingen.de

    2016-04-01

    We compute the distribution of minima that are reached dynamically on multi-field axionic landscapes, both numerically and analytically. Such landscapes are well suited for inflationary model building due to the presence of shift symmetries and possible alignment effects (the KNP mechanism). The resulting distribution of dynamically reached minima differs considerably from the naive expectation based on counti