Cogent Confabulation based Expert System for Segmentation and Classification of Natural Landscape Images

Directory of Open Access Journals (Sweden)

BRAOVIC, M.

2017-05-01

Full Text Available Ever since there has been an increase in the number of automatic wildfire monitoring and surveillance systems in the last few years, natural landscape images have been of great importance. In this paper we propose an expert system for fast segmentation and classification of regions on natural landscape images that is suitable for real-time applications. We focus primarily on Mediterranean landscape images since the Mediterranean area and areas with similar climate are the ones most associated with high wildfire risk. The proposed expert system is based on cogent confabulation theory and knowledge bases that contain information about local and global features, optimal color spaces suitable for classification of certain regions, and context of each class. The obtained results indicate that the proposed expert system significantly outperforms well-known classifiers that it was compared against in both accuracy and speed, and that it is effective and efficient for real-time applications. Additionally, we present a FESB MLID dataset on which we conducted our research and that we made publicly available.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Directory of Open Access Journals (Sweden)

Wei Jin

2016-12-01

Full Text Available 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.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Science.gov (United States)

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

Landscape Hazards in Yukon Communities: Geological Mapping for Climate Change Adaptation Planning

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Kennedy, K.; Kinnear, L.

2010-12-01

Climate change is considered to be a significant challenge for northern communities where the effects of increased temperature and climate variability are beginning to affect infrastructure and livelihoods (Arctic Climate Impact Assessment, 2004). Planning for and adapting to ongoing and future changes in climate will require the identification and characterization of social, economic, cultural, political and biophysical vulnerabilities. This pilot project addresses physical landscape vulnerabilities in two communities in the Yukon Territory through community-scale landscape hazard mapping and focused investigations of community permafrost conditions. Landscape hazards are identified by combining pre-existing data from public utilities and private-sector consultants with new geophysical techniques (ground penetrating radar and electrical resistivity), shallow drilling, surficial geological mapping, and permafrost characterization. Existing landscape vulnerabilities are evaluated based on their potential for hazard (low, medium or high) under current climate conditions, as well as under future climate scenarios. Detailed hazard maps and landscape characterizations for both communities will contribute to overall adaptation plans and allow for informed development, planning and mitigation of potentially threatening hazards in and around the communities.

Adaptive DCTNet for Audio Signal Classification

OpenAIRE

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-01-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to h...

Adaptive Matrices for Color Texture Classification

NARCIS (Netherlands)

Bunte, Kerstin; Giotis, Ioannis; Petkov, Nicolai; Biehl, Michael; Real, P; DiazPernil, D; MolinaAbril, H; Berciano, A; Kropatsch, W

2011-01-01

In this paper we introduce an integrative approach towards color texture classification learned by a supervised framework. Our approach is based on the Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure which is defined in the Fourier domain and 2D Gabor

Mapping agricultural landscapes and characterizing adaptive capacity in Central America

Science.gov (United States)

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

Determination of the ecological connectivity between landscape patches obtained using the knowledge engineer (expert) classification technique

Science.gov (United States)

Selim, Serdar; Sonmez, Namik Kemal; Onur, Isin; Coslu, Mesut

2017-10-01

Connection of similar landscape patches with ecological corridors supports habitat quality of these patches, increases urban ecological quality, and constitutes an important living and expansion area for wild life. Furthermore, habitat connectivity provided by urban green areas is supporting biodiversity in urban areas. In this study, possible ecological connections between landscape patches, which were achieved by using Expert classification technique and modeled with probabilistic connection index. Firstly, the reflection responses of plants to various bands are used as data in hypotheses. One of the important features of this method is being able to use more than one image at the same time in the formation of the hypothesis. For this reason, before starting the application of the Expert classification, the base images are prepared. In addition to the main image, the hypothesis conditions were also created for each class with the NDVI image which is commonly used in the vegetation researches. Besides, the results of the previously conducted supervised classification were taken into account. We applied this classification method by using the raster imagery with user-defined variables. Hereupon, to provide ecological connections of the tree cover which was achieved from the classification, we used Probabilistic Connection (PC) index. The probabilistic connection model which is used for landscape planning and conservation studies via detecting and prioritization critical areas for ecological connection characterizes the possibility of direct connection between habitats. As a result we obtained over % 90 total accuracy in accuracy assessment analysis. We provided ecological connections with PC index and we created inter-connected green spaces system. Thus, we offered and implicated green infrastructure system model takes place in the agenda of recent years.

Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes.

Science.gov (United States)

Rendel, Mark D

2011-01-01

In RNA fitness landscapes with interconnected networks of neutral mutations, neutral precursor mutations can play an important role in facilitating the accessibility of epistatic adaptive mutant combinations. I use an exhaustively surveyed fitness landscape model based on short sequence RNA genotypes (and their secondary structure phenotypes) to calculate the minimum rate at which mutants initially appearing as neutral are incorporated into an adaptive evolutionary walk. I show first, that incorporating neutral mutations significantly increases the number of point mutations in a given evolutionary walk when compared to estimates from previous adaptive walk models. Second, that incorporating neutral mutants into such a walk significantly increases the final fitness encountered on that walk - indeed evolutionary walks including neutral steps often reach the global optimum in this model. Third, and perhaps most importantly, evolutionary paths of this kind are often extremely winding in their nature and have the potential to undergo multiple mutations at a given sequence position within a single walk; the potential of these winding paths to mislead phylogenetic reconstruction is briefly considered. Copyright © 2010 Elsevier Inc. All rights reserved.

Adaptive SVM for Data Stream Classification

Directory of Open Access Journals (Sweden)

Isah A. Lawal

2017-07-01

Full Text Available In this paper, we address the problem of learning an adaptive classifier for the classification of continuous streams of data. We present a solution based on incremental extensions of the Support Vector Machine (SVM learning paradigm that updates an existing SVM whenever new training data are acquired. To ensure that the SVM effectiveness is guaranteed while exploiting the newly gathered data, we introduce an on-line model selection approach in the incremental learning process. We evaluated the proposed method on real world applications including on-line spam email filtering and human action classification from videos. Experimental results show the effectiveness and the potential of the proposed approach.

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

Science.gov (United States)

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data

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Sarah J. Graves

2016-02-01

Full Text Available Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree species distributions at increasingly greater spatial scales. Classification requires a dataset of field observations matched to the image, which will often reflect natural species distributions, resulting in an imbalanced dataset with many samples for common species and few samples for less common species. Despite the high prevalence of imbalanced datasets in multiclass species predictions, the effect on species prediction accuracy and landscape species abundance has not yet been quantified. First, we trained and assessed the accuracy of a support vector machine (SVM model with a highly imbalanced dataset of 20 tropical species and one mixed-species class of 24 species identified in a hyperspectral image mosaic (350–2500 nm of Panamanian farmland and secondary forest fragments. The model, with an overall accuracy of 62% ± 2.3% and F-score of 59% ± 2.7%, was applied to the full image mosaic (23,000 ha at a 2-m resolution to produce a species prediction map, which suggested that this tropical agricultural landscape is more diverse than what has been presented in field-based studies. Second, we quantified the effect of class imbalance on model accuracy. Model assessment showed a trend where species with more samples were consistently over predicted while species with fewer samples were under predicted. Standardizing sample size reduced model accuracy, but also reduced the level of species over- and under-prediction. This study advances operational species mapping of diverse tropical landscapes by detailing the effect of imbalanced data on classification accuracy and providing estimates of tree species abundance in an agricultural landscape. Species maps using data and methods presented here can be used in landscape analyses of species distributions to understand human or environmental effects, in addition to focusing conservation

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

Directory of Open Access Journals (Sweden)

João Lopes Guilherme

Full Text Available 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

Reciprocal sign epistasis between frequently experimentally evolved adaptive mutations causes a rugged fitness landscape.

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Daniel J Kvitek

2011-04-01

Full Text Available The fitness landscape captures the relationship between genotype and evolutionary fitness and is a pervasive metaphor used to describe the possible evolutionary trajectories of adaptation. However, little is known about the actual shape of fitness landscapes, including whether valleys of low fitness create local fitness optima, acting as barriers to adaptive change. Here we provide evidence of a rugged molecular fitness landscape arising during an evolution experiment in an asexual population of Saccharomyces cerevisiae. We identify the mutations that arose during the evolution using whole-genome sequencing and use competitive fitness assays to describe the mutations individually responsible for adaptation. In addition, we find that a fitness valley between two adaptive mutations in the genes MTH1 and HXT6/HXT7 is caused by reciprocal sign epistasis, where the fitness cost of the double mutant prohibits the two mutations from being selected in the same genetic background. The constraint enforced by reciprocal sign epistasis causes the mutations to remain mutually exclusive during the experiment, even though adaptive mutations in these two genes occur several times in independent lineages during the experiment. Our results show that epistasis plays a key role during adaptation and that inter-genic interactions can act as barriers between adaptive solutions. These results also provide a new interpretation on the classic Dobzhansky-Muller model of reproductive isolation and display some surprising parallels with mutations in genes often associated with tumors.

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Science.gov (United States)

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Travelling in the eastern Mediterranean with landscape character assessment

Science.gov (United States)

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.

Adaptive Landscapes of Resistance Genes Change as Antibiotic Concentrations Change.

Science.gov (United States)

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. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Regionalized Development and Maintenance of the Intestinal Adaptive Immune Landscape

DEFF Research Database (Denmark)

Agace, William Winston; McCoy, Kathy D.

2017-01-01

The intestinal immune system has the daunting task of protecting us from pathogenic insults while limiting inflammatory responses against the resident commensal microbiota and providing tolerance to food antigens. This role is particularly impressive when one considers the vast mucosal surface...... and changing landscape that the intestinal immune system must monitor. In this review, we highlight regional differences in the development and composition of the adaptive immune landscape of the intestine and the impact of local intrinsic and environmental factors that shape this process. To conclude, we...... review the evidence for a critical window of opportunity for early-life exposures that affect immune development and alter disease susceptibility later in life....

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

International Nuclear Information System (INIS)

Nowak, Stefan; Krug, Joachim

2015-01-01

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

Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

Science.gov (United States)

Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

2017-07-01

In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

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

Science.gov (United States)

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

Adaptive Matrices and Filters for Color Texture Classification

NARCIS (Netherlands)

Giotis, Ioannis; Bunte, Kerstin; Petkov, Nicolai; Biehl, Michael

In this paper we introduce an integrative approach towards color texture classification and recognition using a supervised learning framework. Our approach is based on Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure, which is defined in the Fourier domain,

Assessment of landscape diversity and determination of landscape hotspots - a case of Slovenia

Science.gov (United States)

Perko, Drago; Ciglič, Rok; Hrvatin, Mauro

2017-04-01

Areas with high landscape diversity can be regarded as landscape hotspots, and vice versa areas with low landscape diversity can be marked as landscape coldspots. The main purpose of this paper is to use quantitative geoinformatical approach and identify parts of our test area (the country of Slovenia) that can be described as very diverse according to natural landscapes and natural elements. We used different digital raster data of natural elements and landscape classifications and defined landscape diversity and landscape hotspots. We defined diversity for each raster pixel by counting the number of different unique types of landscape elements and types of landscapes in its neighborhood. Namely, the method was used separately to define diversity according to natural elements (types of relief forms, rocks, and vegetation) and diversity according to existing geographical landscape classifications of Slovenia (types of landscapes). In both cases one-tenth of Slovenia's surface with the highest landscape diversity was defined as landscape hotspots. The same applies to the coldspots. Additionally we tested the same method of counting different types of landscapes in certain radius also for the area of Europe in order to find areas that are more diverse at continental level. By doing so we were able to find areas that have similar level of diversity as Slovenia according to different European landscape classifications. Areas with landscape diversity may have an advantage in economic development, especially in tourism. Such areas are also important for biodiversity, habitat, and species diversity. On the other hand, localities where various natural influences mix can also be areas where it is hard to transfer best practices from one place to another because of the varying responses of the landscapes to human intervention. Thus it is important to know where areas with high landscape diversity are.

Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States

Directory of Open Access Journals (Sweden)

Joseph St. Peter

2018-03-01

Full Text Available Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a methodology that uses recent advances in spatial analysis software to create a land cover classification over a large region in the southeastern United States at a fine (1 m spatial resolution. This methodology used image texture metrics and principle components derived from National Agriculture Imagery Program (NAIP aerial photographic imagery, visually classified locations, and a softmax neural network model. The model efficiently produced classification surfaces at 1 m resolution across roughly 11.6 million hectares (28.8 million acres with less than 10% average error in modeled probability. The classification surfaces consist of probability estimates of 13 visually distinct classes for each 1 m cell across the study area. This methodology and the tools used in this study constitute a highly flexible fine resolution land cover classification that can be applied across large extents using standard computer hardware, common and open source software and publicly available imagery.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Classification algorithms using adaptive partitioning

KAUST Repository

Binev, Peter; Cohen, Albert; Dahmen, Wolfgang; DeVore, Ronald

2014-01-01

© 2014 Institute of Mathematical Statistics. Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set approximation to the Bayes set and thus fall into the general category of set estimators. In contrast with the most studied tree-based algorithms, which utilize piecewise constant approximation on the generated partition [IEEE Trans. Inform. Theory 52 (2006) 1335.1353; Mach. Learn. 66 (2007) 209.242], we consider decorated trees, which allow us to derive higher order methods. Convergence rates for these methods are derived in terms the parameter - of margin conditions and a rate s of best approximation of the Bayes set by decorated adaptive partitions. They can also be expressed in terms of the Besov smoothness β of the regression function that governs its approximability by piecewise polynomials on adaptive partition. The execution of the algorithms does not require knowledge of the smoothness or margin conditions. Besov smoothness conditions are weaker than the commonly used Holder conditions, which govern approximation by nonadaptive partitions, and therefore for a given regression function can result in a higher rate of convergence. This in turn mitigates the compatibility conflict between smoothness and margin parameters.

Classification algorithms using adaptive partitioning

KAUST Repository

Binev, Peter

2014-12-01

© 2014 Institute of Mathematical Statistics. Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set approximation to the Bayes set and thus fall into the general category of set estimators. In contrast with the most studied tree-based algorithms, which utilize piecewise constant approximation on the generated partition [IEEE Trans. Inform. Theory 52 (2006) 1335.1353; Mach. Learn. 66 (2007) 209.242], we consider decorated trees, which allow us to derive higher order methods. Convergence rates for these methods are derived in terms the parameter - of margin conditions and a rate s of best approximation of the Bayes set by decorated adaptive partitions. They can also be expressed in terms of the Besov smoothness β of the regression function that governs its approximability by piecewise polynomials on adaptive partition. The execution of the algorithms does not require knowledge of the smoothness or margin conditions. Besov smoothness conditions are weaker than the commonly used Holder conditions, which govern approximation by nonadaptive partitions, and therefore for a given regression function can result in a higher rate of convergence. This in turn mitigates the compatibility conflict between smoothness and margin parameters.

Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

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E. Parvinnia

2014-01-01

Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

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

Science.gov (United States)

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)...

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

Science.gov (United States)

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. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Can Public Managers Make Their Welfare Organizations Adapt to the New Performance Landscape Shaped by the Current Austerity?

DEFF Research Database (Denmark)

Pedersen, John Storm; Aagaard, Peter

2014-01-01

How managers try to adapt their organizations to the new performance landscape shaped by the current austerity by new forms of change management in Denmark, in the public sector of citizens with disabilities and socially disadvantaged people.......How managers try to adapt their organizations to the new performance landscape shaped by the current austerity by new forms of change management in Denmark, in the public sector of citizens with disabilities and socially disadvantaged people....

Adaptive testing for making unidimensional and multidimensional classification decisions

NARCIS (Netherlands)

van Groen, M.M.

2014-01-01

Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the examinee’s ability, but they can also be used to classify the examinee into one of two or more levels (e.g. master/non-master). These computerized classification tests have the advantage that they can

Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

Science.gov (United States)

Paneque-Gálvez, Jaime; Mas, Jean-François; Moré, Gerard; Cristóbal, Jordi; Orta-Martínez, Martí; Luz, Ana Catarina; Guèze, Maximilien; Macía, Manuel J.; Reyes-García, Victoria

2013-08-01

Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines - SVM), and hybrid (unsupervised-supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different

Energy landscapes in a crowded world

NARCIS (Netherlands)

Pasqualetti, Martin; Stremke, Sven

2018-01-01

One of the main drivers of landscape transformation has been our demand for energy. We refer to the results of such transformations as "energy landscapes". This paper examines the definition of energy landscapes within a conceptual framework, proposes a classification of energy landscapes, and

Autoregressive Integrated Adaptive Neural Networks Classifier for EEG-P300 Classification

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Demi Soetraprawata

2013-06-01

Full Text Available Brain Computer Interface has a potency to be applied in mechatronics apparatus and vehicles in the future. Compared to the other techniques, EEG is the most preferred for BCI designs. In this paper, a new adaptive neural network classifier of different mental activities from EEG-based P300 signals is proposed. To overcome the over-training that is caused by noisy and non-stationary data, the EEG signals are filtered and extracted using autoregressive models before passed to the adaptive neural networks classifier. To test the improvement in the EEG classification performance with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis. The experiment results show that the all subjects achieve a classification accuracy of 100%.

Domain Adaptation for Opinion Classification: A Self-Training Approach

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Yu, Ning

2013-03-01

Full Text Available Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

Landscape services as boundary concept in landscape governance: Building social capital in collaboration and adapting the landscape

NARCIS (Netherlands)

Westerink, Judith; Opdam, Paul; Rooij, Van Sabine; Steingröver, Eveliene

2017-01-01

The landscape services concept provides a lens to study relations within the social-ecological networks that landscapes are, and to identify stakeholders as either providers or beneficiaries. However, landscape services can also be used as a boundary concept in collaborative landscape governance. We

Adaptation or Resistance: a classification of responses to sea-level rise

Science.gov (United States)

Cooper, J. A.

2016-02-01

Societal responses to sea level rise and associated coastal change are apparently diverse in nature and motivation. Most are commonly referred to as 'adaptation'. Based on a review of current practice, however, it is argued that many of these responses do not involve adaptation, but are rather resisting change. There are several instances where formerly adaptive initiatives involving human adaptability are being replaced by initiatives that resist change. A classification is presented that recognises a continuum of responses ranging from adaptation to resistance, depending upon the willingness to change human activities to accommodate environmental change. In many cases climate change adaptation resources are being used for projects that are purely resistant and which foreclose future adaptation options. It is argued that a more concise definition of adaptation is needed if coastal management is to move beyond the current position of holding the shoreline, other tah n in a few showcase examples.

Research needs for our national landscapes

Science.gov (United States)

Elwood L. Shafer

1979-01-01

The prevailing research problem for our national landscapes is: How shall we organize, control, and coordinate public and private development so as to protect, maintain, improve, and manage those landscape features that we value most? Research questions discussed include: environmental/political conflicts, taxation and zoning, landscape classification, public...

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

Science.gov (United States)

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

Testing adaptive hypotheses of convergence with functional landscapes: a case study of bone-cracking hypercarnivores.

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Zhijie Jack Tseng

Full Text Available 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.

Classification in medical images using adaptive metric k-NN

Science.gov (United States)

Chen, C.; Chernoff, K.; Karemore, G.; Lo, P.; Nielsen, M.; Lauze, F.

2010-03-01

The performance of the k-nearest neighborhoods (k-NN) classifier is highly dependent on the distance metric used to identify the k nearest neighbors of the query points. The standard Euclidean distance is commonly used in practice. This paper investigates the performance of k-NN classifier with respect to different adaptive metrics in the context of medical imaging. We propose using adaptive metrics such that the structure of the data is better described, introducing some unsupervised learning knowledge in k-NN. We investigated four different metrics are estimated: a theoretical metric based on the assumption that images are drawn from Brownian Image Model (BIM), the normalized metric based on variance of the data, the empirical metric is based on the empirical covariance matrix of the unlabeled data, and an optimized metric obtained by minimizing the classification error. The spectral structure of the empirical covariance also leads to Principal Component Analysis (PCA) performed on it which results the subspace metrics. The metrics are evaluated on two data sets: lateral X-rays of the lumbar aortic/spine region, where we use k-NN for performing abdominal aorta calcification detection; and mammograms, where we use k-NN for breast cancer risk assessment. The results show that appropriate choice of metric can improve classification.

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

Science.gov (United States)

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.

Social-ecology networks : building connections for sustainable landscapes

NARCIS (Netherlands)

Opdam, P.F.M.

2014-01-01

Humans adapt their landscapes, their living environment. Sustainable use of the various landscape benefits requires that land owners and users collaborate in managing ecological networks. Because the government is stepping back as the organizer of coordinated landscape adaptation, we need new

Statistical topography of fitness landscapes

OpenAIRE

Franke, Jasper

2011-01-01

Fitness landscapes are generalized energy landscapes that play an important conceptual role in evolutionary biology. These landscapes provide a relation between the genetic configuration of an organism and that organism’s adaptive properties. In this work, global topographical features of these fitness landscapes are investigated using theoretical models. The resulting predictions are compared to empirical landscapes. It is shown that these landscapes allow, at least with respe...

LANDSCAPE PLANNING IN UKRAINE: THE FIRST LANDSCAPE-PLANNING PROGRAM

Directory of Open Access Journals (Sweden)

Leonid Rudenko

2013-01-01

Full Text Available The paper presents the results of the first, in Ukraine; project on landscape planning widely accepted in European countries. Under the project implemented in 2010–2013, a landscape-planning program has been developed for the Cherkassy oblast. This is the first document of this kind in Ukraine. The program is mainly based on the experience of the German and Russian schools of landscape planning and on research and assessment conducted by the authors, which allowed identifying approaches to landscape planning, principles of the national policy, and characteristics and potential of environmentally friendly planning in Ukraine. The paper discusses the main phases of the work on the development of the landscape program for the oblast. It also identifies the main stages and key concepts and principles of landscape planning. The paper presents the results of integrated research on the identification and classification of conflicts in land use and the integral concept of the developmental goals for the oblast. The results can be the foundation for adopting management decisions and development of action plans for the lower hierarchal branches.

Landscape metrics application in ecological and visual landscape assessment

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Gavrilović Suzana

2017-01-01

Full Text Available The development of landscape-ecological approach application in spatial planning provides exact theoretical and empirical evidence for monitoring ecological consequences of natural and/or anthropogenic factors, particularly changes in spatial structures caused by them. Landscape pattern which feature diverse landscape values is the holder of the unique landscape character at different spatial levels and represents a perceptual domain for its users. Using the landscape metrics, the parameters of landscape composition and configuration are mathematical algorithms that quantify the specific spatial characteristics used for interpretation of landscape features and processes (physical and ecological aspect, as well as forms (visual aspect and the meaning (cognitive aspect of the landscape. Landscape metrics has been applied mostly in the ecological and biodiversity assessments as well as in the determination of the level of structural change of landscape, but more and more applied in the assessment of the visual character of the landscape. Based on a review of relevant literature, the aim of this work is to show the main trends of landscape metrics within the aspect of ecological and visual assessments. The research methodology is based on the analysis, classification and systematization of the research studies published from 2000 to 2016, where the landscape metrics is applied: (1 the analysis of landscape pattern and its changes, (2 the analysis of biodiversity and habitat function and (3 a visual landscape assessment. By selecting representative metric parameters for the landscape composition and configuration, for each category is formed the basis for further landscape metrics research and application for the integrated ecological and visual assessment of the landscape values. Contemporary conceptualization of the landscape is seen holistically, and the future research should be directed towards the development of integrated landscape assessment

Content-adaptive pyramid representation for 3D object classification

DEFF Research Database (Denmark)

Kounalakis, Tsampikos; Boulgouris, Nikolaos; Triantafyllidis, Georgios

2016-01-01

In this paper we introduce a novel representation for the classification of 3D images. Unlike most current approaches, our representation is not based on a fixed pyramid but adapts to image content and uses image regions instead of rectangular pyramid scales. Image characteristics, such as depth...... and color, are used for defining regions within images. Multiple region scales are formed in order to construct the proposed pyramid image representation. The proposed method achieves excellent results in comparison to conventional representations....

AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

Science.gov (United States)

Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

2017-09-21

Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

Validating the Danish adaptation of the World Health Organization's International Classification for Patient Safety classification of patient safety incident types

DEFF Research Database (Denmark)

Mikkelsen, Kim Lyngby; Thommesen, Jacob; Andersen, Henning Boje

2013-01-01

Objectives Validation of a Danish patient safety incident classification adapted from the World Health Organizaton's International Classification for Patient Safety (ICPS-WHO). Design Thirty-three hospital safety management experts classified 58 safety incident cases selected to represent all types.......513 (range: 0.193–0.804). Kappa and ICC showed high correlation (r = 0.99). An inverse correlation was found between the prevalence of type and inter-rater reliability. Results are discussed according to four factors known to determine the inter-rater agreement: skill and motivation of raters; clarity...

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

Science.gov (United States)

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.

Energy landscape reveals that the budding yeast cell cycle is a robust and adaptive multi-stage process.

Directory of Open Access Journals (Sweden)

Cheng Lv

2015-03-01

Full Text Available 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.

Landscapes of the Kruger National Park

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W. P. D Gertenbach

1983-12-01

Full Text Available Knowledge on the abiotic and biotic components of the Kruger National Park (KNP system has increased to such an extent, that it was possible to zonate the KNP into landscapes. A landscape was defined as an area with a specific geomorphology, climate, soil and vegetation pattern together with the associated fauna. On this basis 35 landscapes were identified and described in terms of the components mentioned in the definition. The objective of classification is that future management should be based on these landscapes. Relevant management considerations may change, but the landscape a@ a basic functional unit should not be negotiable.

An extension of the classification of evolutionary singular strategies in Adaptive Dynamics

NARCIS (Netherlands)

Boldin, Barbara; Diekmann, Odo

2014-01-01

The existing classification of evolutionarily singular strategies in Adaptive Dynamics (Geritz et al. in Evol Ecol 12:35–57, 1998; Metz et al. in Stochastic and spatial structures of dynamical systems, pp 183–231, 1996) assumes an invasion exponent that is differentiable twice as a function of both

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

Science.gov (United States)

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

2018-02-01

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.

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

Science.gov (United States)

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…

Monitoring and Morphologic Classification of Pediatric Cataract Using Slit-Lamp-Adapted Photography.

Science.gov (United States)

Long, Erping; Lin, Zhuoling; Chen, Jingjing; Liu, Zhenzhen; Cao, Qianzhong; Lin, Haotian; Chen, Weirong; Liu, Yizhi

2017-11-01

To investigate the feasibility of pediatric cataract monitoring and morphologic classification using slit lamp-adapted anterior segmental photography in a large cohort that included uncooperative children. Patients registered in the Childhood Cataract Program of the Chinese Ministry of Health were prospectively selected. Eligible patients underwent slit-lamp adapted anterior segmental photography to record and monitor the morphology of their cataractous lenses. A set of assistance techniques for slit lamp-adapted photography was developed to instruct the parents of uncooperative children how to help maintain the child's head position and keep the eyes open after sleep aid administration. Briefly, slit lamp-adapted photography was completed for all 438 children, including 260 (59.4%) uncooperative children with our assistance techniques. All 746 images of 438 patients successfully confirmed the diagnoses and classifications. Considering the lesion location, pediatric cataract morphologies could be objectively classified into the seven following types: total; nuclear; polar, including two subtypes (anterior and posterior); lamellar; nuclear combined with cortical, including three subtypes (coral-like, dust-like, and blue-dot); cortical; and Y suture. The top three types of unilateral cataracts were polar (55, 42.3%), total (42, 32.3%), and nuclear (23, 17.7%); and the top three types of bilateral cataracts were nuclear (110, 35.8%), total (102, 33.2%), and lamellar (34, 11.1%). Slit lamp-adapted anterior segmental photography is applicable for monitoring and classifying the morphologies of pediatric cataracts and is even safe and feasible for uncooperative children with assistance techniques and sleep aid administration. This study proposes a novel strategy for the preoperative evaluation and evidence-based management of pediatric ophthalmology (Clinical Trials.gov, NCT02748031).

Social-ecology networks : building connections for sustainable landscapes

OpenAIRE

Opdam, P.F.M.

2014-01-01

Humans adapt their landscapes, their living environment. Sustainable use of the various landscape benefits requires that land owners and users collaborate in managing ecological networks. Because the government is stepping back as the organizer of coordinated landscape adaptation, we need new landscape planning approaches that enhance collaboration by building social networks and link them to ecological networks. In this farewell address I will explain why the social-ecological network is a p...

Optimal Decision Fusion for Urban Land-Use/Land-Cover Classification Based on Adaptive Differential Evolution Using Hyperspectral and LiDAR Data

Directory of Open Access Journals (Sweden)

Yanfei Zhong

2017-08-01

Full Text Available Hyperspectral images and light detection and ranging (LiDAR data have, respectively, the high spectral resolution and accurate elevation information required for urban land-use/land-cover (LULC classification. To combine the respective advantages of hyperspectral and LiDAR data, this paper proposes an optimal decision fusion method based on adaptive differential evolution, namely ODF-ADE, for urban LULC classification. In the ODF-ADE framework the normalized difference vegetation index (NDVI, gray-level co-occurrence matrix (GLCM and digital surface model (DSM are extracted to form the feature map. The three different classifiers of the maximum likelihood classifier (MLC, support vector machine (SVM and multinomial logistic regression (MLR are used to classify the extracted features. To find the optimal weights for the different classification maps, weighted voting is used to obtain the classification result and the weights of each classification map are optimized by the differential evolution algorithm which uses a self-adaptive strategy to obtain the parameter adaptively. The final classification map is obtained after post-processing based on conditional random fields (CRF. The experimental results confirm that the proposed algorithm is very effective in urban LULC classification.

Heritage landscape structure analysis in surrounding environment of the Grand Canal Yangzhou section

Science.gov (United States)

Xu, Huan

2018-03-01

The Yangzhou section of the Grand Canal is selected for a case study in this paper. The ZY-3 satellite images of 2016 are adopted as the data source. RS and GIS are used to analyze the landscape classification of the surrounding landscape of the Grand Canal, and the classification results are precisely evaluated. Next, the overall features of the landscape pattern are analyzed. The results showed that the overall accuracy is 82.5% and the Kappa coefficient is 78.17% in the Yangzhou section. The producer’s accuracy of the water landscape is the highest, followed by that of the other landscape, farmland landscape, garden and forest landscape, architectural landscape. The user’s accuracy of different landscape types can be ranked in a descending order, as the water landscape, farmland landscape, road landscape, architectural landscape, other landscape, garden and forest landscape. The farmland landscape and the architectural landscape are the top advantageous landscape types of the heritage site. The research findings can provide basic data for landscape protection, management and sustainable development of the Grand Canal Yangzhou section.

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

Science.gov (United States)

Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa

2018-03-01

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.

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

Science.gov (United States)

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.

Impact of Urban Climate Landscape Patterns on Land Surface Temperature in Wuhan, China

Directory of Open Access Journals (Sweden)

Yasha Wang

2017-09-01

Full Text Available Facing urban warming, mitigation and adaptation strategies are not efficient enough to tackle excessive urban heat, especially at the local scale. The local climate zone (LCZ classification scheme is employed to examine the diversity and complexity of the climate response within a city. This study suggests that zonal practice could be an efficient way to bridge the knowledge gap between climate research and urban planning. Urban surfaces classified by LCZ are designated as urban climate landscapes, which extends the LCZ concept to urban planning applications. Selecting Wuhan as a case study, we attempt to explore the climatic effect of landscape patterns. Thermal effects are compared across the urban climate landscapes, and the relationships between patch metrics and land surface temperature (LST are quantified. Results indicate that climate landscape layout is a considerable factor impacting local urban climate. For Wuhan, 500 m is an optimal scale for exploring landscape pattern-temperature relationships. Temperature contrast between surrounding landscape patches has a major influence on LST. Generally, fragmental landscape patches contribute to heat release. For most climate landscape types, patch metrics also have a significant effect on thermal response. When three metrics are included as predictive variables, 53.3% of the heating intensity variation can be explained for the Large Lowrise landscape, while 57.4% of the cooling intensity variation can be explained for the Water landscape. Therefore, this article claims that land-based layout optimization strategy at local scale, which conforms to planning manner, should be taken into account in terms of heat management.

Landscape Evolution Modelling-LAPSUS

Energy Technology Data Exchange (ETDEWEB)

Baartman, J. E. M.; Temme, A. J. A. M.; Schoorl, J. M.; Claessens, L.; Viveen, W.; Gorp, W. van; Veldkamp, A.

2009-07-01

Landscape evolution modelling can make the consequences of landscape evolution hypotheses explicit and theoretically allows for their falsification and improvement. ideally, landscape evolution models (LEMs) combine the results of all relevant landscape forming processes into an ever-adapting digital landscape (e.g. DEM). These processes may act on different spatial and temporal scales. LAPSUS is such a LEM. Processes that have in different studies been included in LAPSUS are water erosion and deposition, landslide activity, creep, solidification, weathering, tectonics and tillage. Process descriptions are as simple and generic as possible, ensuring wide applicability. (Author) 25 refs.

Landscape Evolution Modelling-LAPSUS

International Nuclear Information System (INIS)

Baartman, J. E. M.; Temme, A. J. A. M.; Schoorl, J. M.; Claessens, L.; Viveen, W.; Gorp, W. van; Veldkamp, A.

2009-01-01

Landscape evolution modelling can make the consequences of landscape evolution hypotheses explicit and theoretically allows for their falsification and improvement. ideally, landscape evolution models (LEMs) combine the results of all relevant landscape forming processes into an ever-adapting digital landscape (e.g. DEM). These processes may act on different spatial and temporal scales. LAPSUS is such a LEM. Processes that have in different studies been included in LAPSUS are water erosion and deposition, landslide activity, creep, solidification, weathering, tectonics and tillage. Process descriptions are as simple and generic as possible, ensuring wide applicability. (Author) 25 refs.

Discrimination of Settlement and Industrial Area Using Landscape Metrics in Rural Region

Directory of Open Access Journals (Sweden)

Xinyu Zheng

2016-10-01

Full Text Available Detailed and precise information of land-use and land-cover (LULC in rural area is essential for land-use planning, environment and energy management. The confusion in mapping residential and industrial areas brings problems in energy management, environmental management and sustainable land use development. However, they remain ambiguous in the former rural LULC mapping, and this insufficient supervision leads to inefficient land exploitation and a great waste of land resources. Hence, the extent and area of residential and industrial cover need to be revealed urgently. However, spectral and textural information is not sufficient for classification heterogeneity due to the similarity between different LULC types. Meanwhile, the contextual information about the relationship between a LULC feature and its surroundings still has potential in classification application. This paper attempts to discriminate settlement and industry area using landscape metrics. A feasible classification scheme integrating landscape metrics, chessboard segmentation and object-based image analysis (OBIA is proposed. First LULC map is generated from GeoEye-1 image, which delineated distribution of different land-cover materials using traditional OBIA method with spectrum and texture information. Then, a chessboard segmentation of the whole LULC map is conducted to create landscape units in a uniform spatial area. Landscape characteristics in each square of chessboard are adopted in the classification algorithm subsequently. To analyze landscape unit scale effect, a variety of chessboard scales are tested, with overall accuracy ranging from 75% to 88%, and Kappa coefficient from 0.51 to 0.76. Optimal chessboard scale is obtained through accuracy assessment comparison. This classification scheme is then compared to two other approaches: a top-down hierarchical classification network using only spectral, textural and shape properties, and lacunarity based hierarchical

Adaptive capacity based water quality resilience transformation and policy implications in rapidly urbanizing landscapes

International Nuclear Information System (INIS)

Li, Yi; Degener, Jan; Gaudreau, Matthew; Li, Yangfan; Kappas, Martin

2016-01-01

Resilience-based management focuses on specific attributes or drivers of complex social-ecological systems, in order to operationalize and promote guiding principles for water quality management in urban systems. We therefore propose a resilience lens drawing on the theory of adaptive capacity and adaptive cycle to evaluate the urban resilience between water quality and land use type. Our findings show that the resilience of water quality variables, which were calculated based on their adaptive capacities, showed adaptive and sustainable trends with dramatic fluctuation. NH_3-N, Cadmium and Total Phosphorus experienced the most vulnerable shifts in the built-up area, agricultural areas, and on bare land. Our framework provided a consistent and repeatable approach to address uncertainty inherent in the resilience of water quality in different landscapes, as well as an approach to monitor variables over time with respect to national water quality standards. Ultimately, we pointed to the political underpinnings for risk mitigation and managing resilient urban system in a particular coastal urban setting. - Highlights: • Integrated framework to analyze the resilience of urban land-water systems • Addressed the changes of adaptive capacity based resilience and transitions • Applied four transition phases of adaptive cycle to water quality management

Adaptive capacity based water quality resilience transformation and policy implications in rapidly urbanizing landscapes

Energy Technology Data Exchange (ETDEWEB)

Li, Yi, E-mail: ly463526@gmail.com [Department of Cartography, GIS and Remote Sensing, Institute of Geography, Georg-August University of Goettingen, Goettingen 37077 (Germany); Key Laboratory of Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment and Ecology, Xiamen University, Xiamen 361102 (China); Degener, Jan [Department of Cartography, GIS and Remote Sensing, Institute of Geography, Georg-August University of Goettingen, Goettingen 37077 (Germany); Gaudreau, Matthew [Balsillie School of International Affairs, Faculty of Environment, University of Waterloo, 67 Erb Street West, Waterloo, ON N2L 6C2 (Canada); Li, Yangfan, E-mail: yangf@xmu.edu.cn [Key Laboratory of Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment and Ecology, Xiamen University, Xiamen 361102 (China); Kappas, Martin [Department of Cartography, GIS and Remote Sensing, Institute of Geography, Georg-August University of Goettingen, Goettingen 37077 (Germany)

2016-11-01

Resilience-based management focuses on specific attributes or drivers of complex social-ecological systems, in order to operationalize and promote guiding principles for water quality management in urban systems. We therefore propose a resilience lens drawing on the theory of adaptive capacity and adaptive cycle to evaluate the urban resilience between water quality and land use type. Our findings show that the resilience of water quality variables, which were calculated based on their adaptive capacities, showed adaptive and sustainable trends with dramatic fluctuation. NH{sub 3}-N, Cadmium and Total Phosphorus experienced the most vulnerable shifts in the built-up area, agricultural areas, and on bare land. Our framework provided a consistent and repeatable approach to address uncertainty inherent in the resilience of water quality in different landscapes, as well as an approach to monitor variables over time with respect to national water quality standards. Ultimately, we pointed to the political underpinnings for risk mitigation and managing resilient urban system in a particular coastal urban setting. - Highlights: • Integrated framework to analyze the resilience of urban land-water systems • Addressed the changes of adaptive capacity based resilience and transitions • Applied four transition phases of adaptive cycle to water quality management.

An Outline of the Evolution of Rural Cultural Landscapes in Poland

Directory of Open Access Journals (Sweden)

KRZYSZTOF KORELESKI

2007-01-01

Full Text Available The paper outlines the evolution of rural cultural landscapes in Poland against the background of landscape classification. It defines cultural landscape types and subtypes, based on several criteria of landscape classification, such as: genetic, morphological, functional, and economic. A review of rural landscapes, based on genetic criteria, considers the following historical periods: the primeval community, the feudalism, the manorial system, the industrial revolution, the interwar period of 1918 – 1939, the period of socialist economy, and market economy. The processes that most significantly influenced the contemporary shape of the rural landscape occurred just after the Second World War: urbanization and industrialization, settlement in western and northern territories, as well as structural and spatial transformations that took place after the year 1989 related to the promotion of sustainable and multifunctional development of rural areas.

Epigenetic Inheritance Across the Landscape

Directory of Open Access Journals (Sweden)

Amy Vaughn Whipple

2016-10-01

Full Text Available 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.

Epigenetic Inheritance across the Landscape.

Science.gov (United States)

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.

MRI-based treatment plan simulation and adaptation for ion radiotherapy using a classification-based approach

International Nuclear Information System (INIS)

Rank, Christopher M; Tremmel, Christoph; Hünemohr, Nora; Nagel, Armin M; Jäkel, Oliver; Greilich, Steffen

2013-01-01

In order to benefit from the highly conformal irradiation of tumors in ion radiotherapy, sophisticated treatment planning and simulation are required. The purpose of this study was to investigate the potential of MRI for ion radiotherapy treatment plan simulation and adaptation using a classification-based approach. Firstly, a voxelwise tissue classification was applied to derive pseudo CT numbers from MR images using up to 8 contrasts. Appropriate MR sequences and parameters were evaluated in cross-validation studies of three phantoms. Secondly, ion radiotherapy treatment plans were optimized using both MRI-based pseudo CT and reference CT and recalculated on reference CT. Finally, a target shift was simulated and a treatment plan adapted to the shift was optimized on a pseudo CT and compared to reference CT optimizations without plan adaptation. The derivation of pseudo CT values led to mean absolute errors in the range of 81 - 95 HU. Most significant deviations appeared at borders between air and different tissue classes and originated from partial volume effects. Simulations of ion radiotherapy treatment plans using pseudo CT for optimization revealed only small underdosages in distal regions of a target volume with deviations of the mean dose of PTV between 1.4 - 3.1% compared to reference CT optimizations. A plan adapted to the target volume shift and optimized on the pseudo CT exhibited a comparable target dose coverage as a non-adapted plan optimized on a reference CT. We were able to show that a MRI-based derivation of pseudo CT values using a purely statistical classification approach is feasible although no physical relationship exists. Large errors appeared at compact bone classes and came from an imperfect distinction of bones and other tissue types in MRI. In simulations of treatment plans, it was demonstrated that these deviations are comparable to uncertainties of a target volume shift of 2 mm in two directions indicating that especially

Identifying the characteristic of SundaParahiyangan landscape for a model of sustainable agricultural landscape

Science.gov (United States)

Dahlan, M. Z.; Nurhayati, H. S. A.; Mugnisjah, W. Q.

2017-10-01

This study was an explorative study of the various forms of traditional ecological knowledge (TEK) of Sundanese people in the context of sustainable agriculture. The qualitative method was used to identify SundaParahiyangan landscape by using Rapid Participatory Rural Appraisal throughsemi-structured interviews, focus group discussions, and field survey. The Landscape Characteristic Assessment and Community Sustainability Assessment were used to analyze the characteristic of landscape to achieve the sustainable agricultural landscape criteria proposed by US Department of Agriculture. The results revealed that the SundaParahiyangan agricultural landscape has a unique characteristic as a result of the long-term adaptation of agricultural society to theirlandscape through a learning process for generations. In general, this character was reflected in the typical of Sundanese’s agroecosystems such as forest garden, mixed garden, paddy field, and home garden. In addition, concept of kabuyutan is one of the TEKs related to understanding and utilization of landscape has been adapted on revitalizing the role of landscape surrounding the agroecosystem as the buffer zone by calculating and designating protected areas. To support the sustainability of production area, integrated practices of agroforestry with low-external-input and sustainable agriculture (LEISA) system can be applied in utilizing and managing agricultural resources.

Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

Directory of Open Access Journals (Sweden)

Inhye Yoon

2015-03-01

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

AN OBJECT-BASED METHOD FOR CHINESE LANDFORM TYPES CLASSIFICATION

Directory of Open Access Journals (Sweden)

H. Ding

2016-06-01

Full Text Available 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.

Physio-climatic classification of South Africa's woodland biome

CSIR Research Space (South Africa)

Fairbanks, DHK

2000-07-01

Full Text Available monthly temperature, total plant-available water balance of soil, elevation, landscape topographic position, and landscape soil fertility were used as input classification variables. The map data were submitted to a factor analysis and varimax axis...

[Dynamic changes of landscape pattern and hemeroby in Ximen Island wetland, Zhejiang Province, China].

Science.gov (United States)

Xiao, Cui; Xie, Xue-Fen; Wu, Tao; Jiang, Guo-Jun; Bian, Hua-Jing; Xu, Wei

2014-11-01

Abstract: The hemeroby type classification system of Ximen Island wetland of Zhejiang Province was established based on the multiple datasets: SOPT-5 image data with a spatial resolution of 5 m in 2007 and 2010, its wetland land cover and land use status, the National Land Use Classification (on trail), and sea area use classification of marine industry standards as well as remote sensing data features. Meanwhile, the dynamic relationship between the landscape pattern and the degree of hemeroby in Ximen Island was investigated with the landscape indices and hemeroby index (HI) derived from the landscape pattern index and GIS spatial analysis. The results showed that the wetland landscape spatial heterogeneity, fragmentation and dominance index dropped, and the landscape shape index complexity was low. The human disturbance center developed from a dispersion type to a concentration type. The landscape type of the disturbance center was bare land and settlement. The HI rose up from the sea to the land. Settlement, wharf and traffic land had the highest HI. The HI of the mudflat cultivation, mudflats and raft-cultivation dramatically changed. Marine-terrestrial interlaced zone showed a low total HI with unstable characteristics. The number of patches declined of undisturbed, partially disturbed and completely disturbed landscapes. Mean patch areas of partially disturbed and completely disturbed landscapes increased, and that of the undisturbed decreased. Mean shape index of the undisturbed landscape decreased, while the partially disturbed and completely disturbed landscapes showed a trend of shape complication.

Channel Classification across Arid West Landscapes in Support of OHW Delineation

Science.gov (United States)

2013-01-01

perspective at Agua Fria River, AZ ...................................................................... 24 Figure 12. Landscape perspective at...27 Figure 16. Active channel at Agua Fria River, AZ...33 Figure 24. Landscape perspective at Agua Fria River, AZ

Navigating the Interface Between Landscape Genetics and Landscape Genomics

Directory of Open Access Journals (Sweden)

Andrew Storfer

2018-03-01

Full Text Available As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species

Adaptive threshold-based shadow masking for across-date settlement classification of panchromatic quickBird images

CSIR Research Space (South Africa)

Luus, FPS

2014-06-01

Full Text Available -1 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 11, NO. 6, JUNE 2014 1153 Adaptive Threshold-Based Shadow Masking for Across- Date Settlement Classification of Panchromatic QuickBird Images F. P. S. Luus, F. van den Bergh, and B. T. J. Maharaj...

Characterising landscape variation through spatial folksonomies

OpenAIRE

Derungs, Curdin; Purves, Ross S

2016-01-01

Describing current, past and future landscapes for inventory and policy making purposes requires classifications capturing variation in, for example, land use and land cover. Typical land cover classifi- cations for such purposes result from a top-down process and rely on expert conceptualisations, and thus provide limited space for incorporating more widely held views of key landscape elements. In this paper we introduce the notion of spatial folksonomies, which we define as a tuple linking ...

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

Science.gov (United States)

Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

2017-08-29

In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

Quantitative analyses of empirical fitness landscapes

International Nuclear Information System (INIS)

Szendro, Ivan G; Franke, Jasper; Krug, Joachim; Schenk, Martijn F; De Visser, J Arjan G M

2013-01-01

The concept of a fitness landscape is a powerful metaphor that offers insight into various aspects of evolutionary processes and guidance for the study of evolution. Until recently, empirical evidence on the ruggedness of these landscapes was lacking, but since it became feasible to construct all possible genotypes containing combinations of a limited set of mutations, the number of studies has grown to a point where a classification of landscapes becomes possible. The aim of this review is to identify measures of epistasis that allow a meaningful comparison of fitness landscapes and then apply them to the empirical landscapes in order to discern factors that affect ruggedness. The various measures of epistasis that have been proposed in the literature appear to be equivalent. Our comparison shows that the ruggedness of the empirical landscape is affected by whether the included mutations are beneficial or deleterious and by whether intragenic or intergenic epistasis is involved. Finally, the empirical landscapes are compared to landscapes generated with the rough Mt Fuji model. Despite the simplicity of this model, it captures the features of the experimental landscapes remarkably well. (paper)

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

Science.gov (United States)

Wendel, Jochen; Buttenfield, Barbara P.; Stanislawski, Larry V.

2016-01-01

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Learning free energy landscapes using artificial neural networks.

Science.gov (United States)

Sidky, Hythem; Whitmer, Jonathan K

2018-03-14

Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis sets which hinder their ability to efficiently conform to varied free energy landscapes. Further, user-specified parameters are in general non-intuitive yet significantly affect the convergence rate and accuracy of the free energy estimate. Here we propose a novel method, wherein artificial neural networks (ANNs) are used to develop an adaptive biasing potential which learns free energy landscapes. We demonstrate that this method is capable of rapidly adapting to complex free energy landscapes and is not prone to boundary or oscillation problems. The method is made robust to hyperparameters and overfitting through Bayesian regularization which penalizes network weights and auto-regulates the number of effective parameters in the network. ANN sampling represents a promising innovative approach which can resolve complex free energy landscapes in less time than conventional approaches while requiring minimal user input.

Learning free energy landscapes using artificial neural networks

Science.gov (United States)

Sidky, Hythem; Whitmer, Jonathan K.

2018-03-01

Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis sets which hinder their ability to efficiently conform to varied free energy landscapes. Further, user-specified parameters are in general non-intuitive yet significantly affect the convergence rate and accuracy of the free energy estimate. Here we propose a novel method, wherein artificial neural networks (ANNs) are used to develop an adaptive biasing potential which learns free energy landscapes. We demonstrate that this method is capable of rapidly adapting to complex free energy landscapes and is not prone to boundary or oscillation problems. The method is made robust to hyperparameters and overfitting through Bayesian regularization which penalizes network weights and auto-regulates the number of effective parameters in the network. ANN sampling represents a promising innovative approach which can resolve complex free energy landscapes in less time than conventional approaches while requiring minimal user input.

Ecosystem services in changing landscapes: An introduction

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Louis Iverson; Cristian Echeverria; Laura Nahuelhual; Sandra. Luque

2014-01-01

The concept of ecosystem services from landscapes is rapidly gaining momentum as a language to communicate values and benefits to scientists and lay alike. Landscape ecology has an enormous contribution to make to this field, and one could argue, uniquely so. Tools developed or adapted for landscape ecology are being increasingly used to assist with the quantification...

Social-Ecological Transformation for Ecosystem Management: the Development of Adaptive Co-management of a Wetland Landscape in Southern Sweden

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Per Olsson

2004-12-01

Full Text Available We analyze the emergence of an adaptive co-management system for wetland landscape governance in southern Sweden, a process where unconnected management by several actors in the landscape was mobilized, renewed, and reconfigured into ecosystem management within about a decade. Our analysis highlights the social mechanisms behind the transformation toward ecosystem management. The self-organizing process was triggered by perceived threats among members of various local stewardship associations and local government to the area's cultural and ecological values. These threats challenged the development of ecosystem services in the area. We show how one individual, a key leader, played an instrumental role in directing change and transforming governance. The transformation involved three phases: 1 preparing the system for change, 2 seizing a window of opportunity, and 3 building social-ecological resilience of the new desired state. This local policy entrepreneur initiated trust-building dialogue, mobilized social networks with actors across scales, and started processes for coordinating people, information flows and ongoing activities, and for compiling and generating knowledge, understanding, and management practices of ecosystem dynamics. Understanding, collaborative learning, and creating public awareness were part of the process. A comprehensive framework was developed with a shared vision and goals that presented conservation as development, turned problems into possibilities, and contributed to a shift in perception among key actors regarding the values of the wetland landscape. A window of opportunity at the political level opened, which made it possible to transform the governance system toward a trajectory of ecosystem management. The transformation involved establishing a new municipal organization, the Ecomuseum Kristianstads Vattenrike (EKV. This flexible organization serves as a bridge between local actors and governmental bodies and is

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

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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

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.

Landscape classification of Huelva (Spain: An objective method of identification and characterization

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Alcántara Manzanares, Jorge

2015-12-01

Full Text Available This study sought to classify the landscape of the province of Huelva (Andalusia, Spain and validate the results, using a new application of classical multivariate methods in conjunction with GIS tools. The province was divided into 1 km x 1 km grid squares to which information was associated on four visually-perceivable variables: soil use, plant cover, lithology and relief. Grid cells were then classified using twoway indicator species analysis (TWINSPAN and ordered by detrended correspondence analysis (DCA. Analysis of results yielded 8 major landscape types that were characterized by its indicator variables. This classification was checked by Discriminant Analysis, which yielded an 80% match with the TWINSPAN estimate.Este estudio trata de clasificar el paisaje de la provincia de Huelva (Andalucía, España y validar los resultados, mediante una nueva aplicación de métodos multivariantes clásicos en combinación con herramientas SIG. La provincia se dividió en cuadrículas de 1 km x 1 km a las que se asoció la información relativa a cuatro variables perceptibles visualmente: usos del suelo, coberturas vegetales, litología y relieve. Las cuadrículas se clasificaron utilizando el análisis de especies indicadoras de doble vía (TWINSPAN y se ordenaron mediante el análisis de correspondencia escalado (DCA. El análisis de los resultados dio lugar a 8 tipos de paisaje que se caracterizaron gracias a sus variables indicadoras. Esta clasificación se validó mediante un análisis discriminante, que coincidió en un 80% con la estimación del TWINSPAN. [fr] Cette étude visait à classer le paysage de la province de Huelva (Andalousie, Espagne et de valider les résultats, à l’aide d’une nouvelle application de méthodes multivariées classiques avec des outils SIG. La province a été divisée en 1 km x 1 km carrés de la grille dans laquelle l’information a été associée à quatre variables visuellement perceptibles: l�

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.

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Hsin-Hung Chou

2014-02-01

Full Text Available How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

2D/3D video content adaptation decision engine based on content classification and user assessment

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Fernandes, Rui; Andrade, M. T.

2017-07-01

Multimedia adaptation depends on several factors, such as the content itself, the consumption device and its characteristics, the transport and access networks and the user. An adaptation decision engine, in order to provide the best possible Quality of Experience to a user, needs to have information about all variables that may influence its decision. For the aforementioned factors, we implement content classification, define device classes, consider limited bandwidth scenarios and categorize user preferences based on a subjective quality evaluation test. The results of these actions generate vital information to pass to the adaptation decision engine so that its operation may provide the indication of the most suitable adaptation to perform that delivers the best possible outcome for the user under the existing constraints.

Hierarchic levels of a system classification of radiation-contaminated landscapes

International Nuclear Information System (INIS)

Dolyin, V.V.; Sushchik, Yu.Ya.; Bondarenko, G.M.; Shramenko, Yi.F.; Dudar, T.V.

2001-01-01

Five hierarchic levels of the systematic organization of natural landscapes are determined: substantial-phase, soil-profile, biogeocenotic, landscape, and geosystematic. Systems and subsystems of compounds of chemical elements and natural and man-caused factors that characterized properties and mechanisms of ecological self-organization of biogeocenoses are brought into accordance with each level. A scheme of hierarchic subordination of systems, subsystems, and processes is worked out. Leading links of transformation and migration of radionuclides that define the contamination of tropic chains are determined

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

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

2017-11-01

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 paper 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.

Thermodynamical interpretation of an adaptive walk on a Mt. Fuji-type fitness landscape: Einstein relation-like formula holds in a stochastic evolution.

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Aita, Takuyo; Husimi, Yuzuru

2003-11-21

We have theoretically studied the statistical properties of adaptive walks (or hill-climbing) on a Mt. Fuji-type fitness landscape in the multi-dimensional sequence space through mathematical analysis and computer simulation. The adaptive walk is characterized by the "mutation distance" d as the step-width of the walker and the "population size" N as the number of randomly generated d-fold point mutants to be screened. In addition to the fitness W, we introduced the following quantities analogous to thermodynamical concepts: "free fitness" G(W) is identical with W+T x S(W), where T is the "evolutionary temperature" T infinity square root of d/lnN and S(W) is the entropy as a function of W, and the "evolutionary force" X is identical with d(G(W)/T)/dW, that is caused by the mutation and selection pressure. It is known that a single adaptive walker rapidly climbs on the fitness landscape up to the stationary state where a "mutation-selection-random drift balance" is kept. In our interpretation, the walker tends to the maximal free fitness state, driven by the evolutionary force X. Our major findings are as follows: First, near the stationary point W*, the "climbing rate" J as the expected fitness change per generation is described by J approximately L x X with L approximately V/2, where V is the variance of fitness distribution on a local landscape. This simple relationship is analogous to the well-known Einstein relation in Brownian motion. Second, the "biological information gain" (DeltaG/T) through adaptive walk can be described by combining the Shannon's information gain (DeltaS) and the "fitness information gain" (DeltaW/T).

Landscape analysis: Theoretical considerations and practical needs

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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.

Adaptive partial volume classification of MRI data

International Nuclear Information System (INIS)

Chiverton, John P; Wells, Kevin

2008-01-01

Tomographic biomedical images are commonly affected by an imaging artefact known as the partial volume (PV) effect. The PV effect produces voxels composed of a mixture of tissues in anatomical magnetic resonance imaging (MRI) data resulting in a continuity of these tissue classes. Anatomical MRI data typically consist of a number of contiguous regions of tissues or even contiguous regions of PV voxels. Furthermore discontinuities exist between the boundaries of these contiguous image regions. The work presented here probabilistically models the PV effect using spatial regularization in the form of continuous Markov random fields (MRFs) to classify anatomical MRI brain data, simulated and real. A unique approach is used to adaptively control the amount of spatial regularization imposed by the MRF. Spatially derived image gradient magnitude is used to identify the discontinuities between image regions of contiguous tissue voxels and PV voxels, imposing variable amounts of regularization determined by simulation. Markov chain Monte Carlo (MCMC) is used to simulate the posterior distribution of the probabilistic image model. Promising quantitative results are presented for PV classification of simulated and real MRI data of the human brain.

Leisuring landscapes : On emergence, transitions and adaptation

NARCIS (Netherlands)

Hartman, S.

2016-01-01

The leisure economy, consisting of the industry cluster of tourism, recreation and leisure, transforms the spatial and socio-economic landscapes of many regions. As a result, regions are ‘leisuring’, experiencing on-going transformative processes that are designed to foster touristic, recreational

Combinatorial vector fields and the valley structure of fitness landscapes.

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Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

From climate-smart agriculture to climate-smart landscapes

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Scherr Sara J

2012-08-01

Full Text Available Abstract Background For agricultural systems to achieve climate-smart objectives, including improved food security and rural livelihoods as well as climate change adaptation and mitigation, they often need to be take a landscape approach; they must become ‘climate-smart landscapes’. Climate-smart landscapes operate on the principles of integrated landscape management, while explicitly incorporating adaptation and mitigation into their management objectives. Results An assessment of climate change dynamics related to agriculture suggests that three key features characterize a climate-smart landscape: climate-smart practices at the field and farm scale; diversity of land use across the landscape to provide resilience; and management of land use interactions at landscape scale to achieve social, economic and ecological impacts. To implement climate-smart agricultural landscapes with these features (that is, to successfully promote and sustain them over time, in the context of dynamic economic, social, ecological and climate conditions requires several institutional mechanisms: multi-stakeholder planning, supportive landscape governance and resource tenure, spatially-targeted investment in the landscape that supports climate-smart objectives, and tracking change to determine if social and climate goals are being met at different scales. Examples of climate-smart landscape initiatives in Madagascar’s Highlands, the African Sahel and Australian Wet Tropics illustrate the application of these elements in contrasting contexts. Conclusions To achieve climate-smart landscape initiatives widely and at scale will require strengthened technical capacities, institutions and political support for multi-stakeholder planning, governance, spatial targeting of investments and multi-objective impact monitoring.

Spatially-Explicit Bayesian Information Entropy Metrics for Calibrating Landscape Transformation Models

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Kostas Alexandridis

2013-06-01

Full Text Available Assessing spatial model performance often presents challenges related to the choice and suitability of traditional statistical methods in capturing the true validity and dynamics of the predicted outcomes. The stochastic nature of many of our contemporary spatial models of land use change necessitate the testing and development of new and innovative methodologies in statistical spatial assessment. In many cases, spatial model performance depends critically on the spatially-explicit prior distributions, characteristics, availability and prevalence of the variables and factors under study. This study explores the statistical spatial characteristics of statistical model assessment of modeling land use change dynamics in a seven-county study area in South-Eastern Wisconsin during the historical period of 1963–1990. The artificial neural network-based Land Transformation Model (LTM predictions are used to compare simulated with historical land use transformations in urban/suburban landscapes. We introduce a range of Bayesian information entropy statistical spatial metrics for assessing the model performance across multiple simulation testing runs. Bayesian entropic estimates of model performance are compared against information-theoretic stochastic entropy estimates and theoretically-derived accuracy assessments. We argue for the critical role of informational uncertainty across different scales of spatial resolution in informing spatial landscape model assessment. Our analysis reveals how incorporation of spatial and landscape information asymmetry estimates can improve our stochastic assessments of spatial model predictions. Finally our study shows how spatially-explicit entropic classification accuracy estimates can work closely with dynamic modeling methodologies in improving our scientific understanding of landscape change as a complex adaptive system and process.

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

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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

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

Science.gov (United States)

Santos, José; Monteagudo, Ángel

2017-03-27

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

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

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Hui Liu

2015-01-01

Full Text Available 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.

The Value of Landscape Essence

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Maria da Conceição Marques Freire

2014-08-01

Full Text Available A new approach to interpreting the landscape is examined by accepting its complexity through inductive reasoning. While attempting to identify the essence of the landscape in the city and municipality of Óbidos, Portugal, several architectural recommendations of Venturi (2004 have been adapted as a framework for understanding this landscape. These will then guide the process of landscape transformation through:•••using the concepts of closed and contained spaces and the concept of fluid space;•recognising the existence of interstitial open spaces;•using those elements which are common to the distinct typologies of space;•defining the components that should be respected and those that can be respected;•observing landscape as a whole , while emphasising the relationship between the parts and the whole; and•rejecting simplification in the landscape transformation process.valuing the ambiguity incorporating the complexity Underlying this approach is the belief that the process of transformation must be based on the essence of each landscape. This implies the use of elements and structures of the landscape which are related to ecological, morphological and cultural systems. These elements and structures represent points of reference which should be considered in the process of landscape transformation.

A method to incorporate uncertainty in the classification of remote sensing images

OpenAIRE

Gonçalves, Luísa M. S.; Fonte, Cidália C.; Júlio, Eduardo N. B. S.; Caetano, Mario

2009-01-01

The aim of this paper is to investigate if the incorporation of the uncertainty associated with the classification of surface elements into the classification of landscape units (LUs) increases the results accuracy. To this end, a hybrid classification method is developed, including uncertainty information in the classification of very high spatial resolution multi-spectral satellite images, to obtain a map of LUs. The developed classification methodology includes the following...

Modeling Aquatic Macroinvertebrate Richness Using Landscape Attributes

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Marcia S. Meixler

2015-01-01

Full Text Available We used a rapid, repeatable, and inexpensive geographic information system (GIS approach to predict aquatic macroinvertebrate family richness using the landscape attributes stream gradient, riparian forest cover, and water quality. Stream segments in the Allegheny River basin were classified into eight habitat classes using these three landscape attributes. Biological databases linking macroinvertebrate families with habitat classes were developed using life habits, feeding guilds, and water quality preferences and tolerances for each family. The biological databases provided a link between fauna and habitat enabling estimation of family composition in each habitat class and hence richness predictions for each stream segment. No difference was detected between field collected and modeled predictions of macroinvertebrate families in a paired t-test. Further, predicted stream gradient, riparian forest cover, and total phosphorus, total nitrogen, and suspended sediment classifications matched observed classifications much more often than by chance alone. High gradient streams with forested riparian zones and good water quality were predicted to have the greatest macroinvertebrate family richness and changes in water quality were predicted to have the greatest impact on richness. Our findings indicate that our model can provide meaningful landscape scale macroinvertebrate family richness predictions from widely available data for use in focusing conservation planning efforts.

BATS AND BT INSECT RESISTANCE ON AGRICULTURAL LANDSCAPES

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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...

Landscape Dynamics on the Island of La Gonave, Haiti, 1990–2010

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Lisa M. Kennedy

2013-09-01

Full Text Available The island of La Gonave lies northwest of Port-au-Prince and is representative of the subsistence Haitian lifestyle. Little is known about the land cover changes and conversion rates on La Gonave. Using Landsat images from 1990 to 2010, this research investigates landscape dynamics through image classification, change detection, and landscape pattern analysis. Five land cover classes were considered: Agriculture, Forest/Dense Vegetation (DV, Shrub, Barren/Eroded, and Nonforested Wetlands. Overall image classification accuracy was 87%. Results of land cover change analysis show that all major land cover types experienced substantial changes from 1990 to 2010. The area percent change was −39.7, −22.7, 87.4, and −7.0 for Agriculture, Forest/Dense Vegetation, Shrub, and Barren/Eroded. Landscape pattern analysis illustrated the encroachment of Shrub cover in core Forest/DV patches and the decline of Agricultural patch integrity. Agricultural abandonment, deforestation, and forest regrowth combined to generate a dynamic island landscape, resulting in higher levels of land cover fragmentation.

Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

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Mailys Lopes

2017-07-01

Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

Application of Source-Sink Landscape Influence Values to Commuter Traffic: A Case Study of Xiamen Island

OpenAIRE

Tong Wu; Lina Tang; Huaxiang Chen; Ziyan Wang; Quanyi Qiu

2017-01-01

Landscape patterns are closely related to ecological processes. Different spatial scales and research methods may lead to different results. Therefore, it is crucial to choose suitable research methods when studying different landscape patterns and ecological processes. In the present study, the methods of source-sink landscape theory were applied to the interactions between urban landscape characteristics and commuter traffic behavior around the arterial roads in Xiamen Island. After classif...

Evolutionary Effect on the Embodied Beauty of Landscape Architectures.

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Zhang, Wei; Tang, Xiaoxiang; He, Xianyou; Chen, Guangyao

2018-01-01

According to the framework of evolutionary aesthetics, a sense of beauty is related to environmental adaptation and plasticity of human beings, which has adaptive value and biological foundations. Prior studies have demonstrated that organisms derive benefits from the landscape. In this study, we investigated whether the benefits of landscape might elicit a stronger sense of beauty and what the nature of this sense of beauty is. In two experiments, when viewing classical landscape and nonlandscape architectures photographs, participants rated the aesthetic scores (Experiment 1) and had a two-alternative forced choice aesthetic judgment by pressing the reaction button located near to (15 cm) or far from (45 cm) the presenting stimuli (Experiment 2). The results showed that reaction of aesthetic ratings for classical landscape architectures was faster than those of classical nonlandscape architectures. Furthermore, only the reaction of beautiful judgment of classical landscape architecture photograph was significantly faster when the reaction button was in the near position to the presenting photograph than those in the position of far away from the presenting photograph. This finding suggests a facilitated effect for the aesthetic perception of classical landscape architectures due to their corresponding components including water and green plants with strong evolutionary implications. Furthermore, this sense of beauty for classical landscape architectures might be the embodied approach to beauty based on the viewpoint of evolutionary aesthetics and embodied cognition.

Applicability of Hydrologic Landscapes for Model Calibration ...

Science.gov (United States)

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

Enhancing Classification Performance of Functional Near-Infrared Spectroscopy- Brain–Computer Interface Using Adaptive Estimation of General Linear Model Coefficients

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Nauman Khalid Qureshi

2017-07-01

Full Text Available In this paper, a novel methodology for enhanced classification of functional near-infrared spectroscopy (fNIRS signals utilizable in a two-class [motor imagery (MI and rest; mental rotation (MR and rest] brain–computer interface (BCI is presented. First, fNIRS signals corresponding to MI and MR are acquired from the motor and prefrontal cortex, respectively, afterward, filtered to remove physiological noises. Then, the signals are modeled using the general linear model, the coefficients of which are adaptively estimated using the least squares technique. Subsequently, multiple feature combinations of estimated coefficients were used for classification. The best classification accuracies achieved for five subjects, for MI versus rest are 79.5, 83.7, 82.6, 81.4, and 84.1% whereas those for MR versus rest are 85.5, 85.2, 87.8, 83.7, and 84.8%, respectively, using support vector machine. These results are compared with the best classification accuracies obtained using the conventional hemodynamic response. By means of the proposed methodology, the average classification accuracy obtained was significantly higher (p < 0.05. These results serve to demonstrate the feasibility of developing a high-classification-performance fNIRS-BCI.

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

OpenAIRE

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 supervi...

Understanding the socio-institutional context to support adaptation for future water security in forest landscapes

Directory of Open Access Journals (Sweden)

Tahia Devisscher

2016-12-01

Full Text Available During the first half of the 21st century, socioeconomic development is expected to contribute faster and to a greater extent to global water stress than climate change. Consequently, we aimed to identify conditions that can facilitate local adaptation planning for future water security, accounting for the socio-institutional context, developmental needs, and interests affecting water use and management. Our study focused on three forest landscapes in Latin America where water stress was identified as a current concern potentially leading to future social conflict if not addressed. In the three sites, we adopted a participatory approach to implement a systematic diagnostic framework for the analysis of socio-institutional barriers and opportunities influencing local adaptation decision making. This novel application enabled science-society engagement in which civil society organizations were coleading the research. The field methods we used involved participatory social network mapping, semistructured interviews, and validation workshops. Our study generated insights into several interventions that could help overcome barriers affecting the adaptation decision-making process, particularly in the diagnosis and early planning phases. Points of intervention included fostering local participation and dialogue to facilitate coproduction of knowledge, and strengthening the role of key central actors in the water governance networks. These key actors are currently bridging multiple interests, information sources, and governance levels, and thus, they could become agents of change that facilitate local adaptation processes. Working jointly with civil society to frame the research proved effective to increase awareness about water issues, which related not only to the technological, economic, and political aspects of water, but also to organizational processes. The involvement of civil society created genuine interest in building further capacity for

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics.

Science.gov (United States)

Esbah, Hayriye; Deniz, Bulent; Kara, Baris; Kesgin, Birsen

2010-06-01

Bafa Lake Nature Park is one of Turkey's most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural-natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.

Adaptation to Climate Change in Panchase Mountain Ecological Regions of Nepal

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Shankar Adhikari

2018-03-01

Full Text Available Rural mountain communities in developing countries are considered particularly vulnerable to environmental change, including climate change. Forests and agriculture provide numerous ecosystem goods and services (EGS to local communities and can help people adapt to the impacts of climate change. There is however poor documentation on the role of EGS in people’s livelihood and adaptation practices. This study in the rural Panchase Mountain Ecological Region of Nepal identifies practices being used to adapt to a changing environment through key informant interviews and focus group discussions. At the household level, livelihood diversification, changes in cropping patterns and farming practices, use of multipurpose plant species and income-generation activities were identified as adaptation strategies. Among major strategies at the community level were community forestry-based climate adaptation plans of action for forest and water resource management. Landscape-level adaptation strategies were large-scale collaborative projects and programs, such as Ecosystem-based Adaptation and Chitwan Annapurna Landscape conservation; which had implications at both the local and landscape-level. A proper blending and integration of adaptation strategies from individual households through to the community and to the landscape level is needed for implementing effective adaptation in the region.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects.

Science.gov (United States)

Kim, Jinkwon; Min, Se Dong; Lee, Myoungho

2011-06-27

Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects

Directory of Open Access Journals (Sweden)

Min Se Dong

2011-06-01

Full Text Available Abstract Background Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. Methods In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. Results A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. Conclusions The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

Landscape metrics for three-dimension urban pattern recognition

Science.gov (United States)

Liu, M.; Hu, Y.; Zhang, W.; Li, C.

2017-12-01

Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.

Examining Social Adaptations in a Volatile Landscape in Northern Mongolia via the Agent-Based Model Ger Grouper

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Julia K. Clark

2015-03-01

Full Text Available The environment of the mountain-steppe-taiga of northern Mongolia is often characterized as marginal because of the high altitude, highly variable precipitation levels, low winter temperatures, and periodic droughts coupled with severe winter storms (known as dzuds. Despite these conditions, herders have inhabited this landscape for thousands of years, and hunter-gatherer-fishers before that. One way in which the risks associated with such a challenging and variable landscape are mitigated is through social networks and inter-family cooperation. We present an agent-based simulation, Ger Grouper, to examine how households have mitigated these risks through cooperation. The Ger Grouper simulation takes into account locational decisions of households, looks at fission/fusion dynamics of households and how those relate to environmental pressures, and assesses how degrees of relatedness can influence sharing of resources during harsh winters. This model, coupled with the traditional archaeological and ethnographic methods, helps shed light on the links between early Mongolian pastoralist adaptations and the environment. While preliminary results are promising, it is hoped that further development of this model will be able to characterize changing land-use patterns as social and political networks developed.

Patterns among the ashes: Exploring the relationship between landscape pattern and the emerald ash borer

Science.gov (United States)

Susan J. Crocker; Dacia M. Meneguzzo; Greg C. Liknes

2010-01-01

Landscape metrics, including host abundance and population density, were calculated using forest inventory and land cover data to assess the relationship between landscape pattern and the presence or absence of the emerald ash borer (EAB) (Agrilus planipennis Fairmaire). The Random Forests classification algorithm in the R statistical environment was...

From Co-Management to Landscape Governance: Whither Ghana’s Modified Taungya System?

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Mirjam A. F. Ros-Tonen

2014-12-01

Full Text Available Natural resource management literature has documented three paradigm shifts over the past decade: from co-management to adaptive co-management and adaptive governance respectively and, more recently, towards landscape governance. The latter is conceived as a governance approach towards negotiated land use at the landscape level to deal with global challenges such as food insecurity, climate change and biodiversity loss. There is not a lot of clarity about how co-management systems could actually evolve into landscape governance. This paper aims to address the gap by exploring how a stalled co-management system for the reforestation of degraded forest areas—the modified taungya system (MTS in Ghana—could be revitalised and redesigned as a landscape approach. Drawing on case studies and expert consultation, the performance of the national MTS and the MTS under the Community Forestry Management Project is reviewed with regard to five principles (integrated approach, multi-stakeholder negotiation, polycentric governance, continual learning and adaptive capacity and three enabling conditions (social capital, bridging organisations and long-term funding distilled from the literature. The authors conclude that some of these principles and conditions were met under the Community Forestry Management Project, but that continual learning, transcending jurisdictional boundaries, developing adaptive capacity, and long-term funding and benefits still pose challenges.

The assignment of occupation densities and the rural soil classification in the territorial classification plans

International Nuclear Information System (INIS)

Velez R, Luis Anibal; Largacha R, Antonio

2003-01-01

Regulations concerning land use density controls in non-urban areas are often ineffective in protecting the rural character of such areas, within the context of Colombia's territorial organization plans What they tend to do is indirectly promote urban expansion through the fixing of minimum plot sizes Rather than question the methods employed in land use classification, the present study uses the case of the rural area of Santa Elena on the outskirts of Medellin and the existing zoning controls as established in the territorial organization plan, and focuses on the regulations established for each land use category as they effect occupation densities and patterns of plot fragmentation. On the one hand a simulation is undertaken of the trends which would result from land occupation in accordance with existing regulations concerning land use classification and plot size This indicates that the overall effect would be to disperse settlement patterns and fragment the landscape Secondly, an alternative scenario is developed based on the modification of minimum plot sizes for each of the three land use classifications established in the existing plan (protection, rural and suburban) In this way, and through the perspective of landscape ecology, It Is shown that in certain cases less dispersion and greater concentration of settlements can be achieved, and in other cases dispersion is minimized The use of GIS is fundamental in the development of such simulation techniques

Landscape sensitivity in a dynamic environment

Science.gov (United States)

Lin, Jiun-Chuan; Jen, Chia-Horn

2010-05-01

Landscape sensitivity at different scales and topics is presented in this study. Methodological approach composed most of this paper. According to the environmental records in the south eastern Asia, the environment change is highly related with five factors, such as scale of influence area, background of environment characters, magnitude and frequency of events, thresholds of occurring hazards and influence by time factor. This paper tries to demonstrate above five points from historical and present data. It is found that landscape sensitivity is highly related to the degree of vulnerability of the land and the processes which put on the ground including human activities. The scale of sensitivity and evaluation of sensitivities is demonstrated in this paper by the data around east Asia. The methods of classification are mainly from the analysis of environmental data and the records of hazards. From the trend of rainfall records, rainfall intensity and change of temperature, the magnitude and frequency of earthquake, dust storm, days of draught, number of hazards, there are many coincidence on these factors with landscape sensitivities. In conclusion, the landscape sensitivities could be classified as four groups: physical stable, physical unstable, unstable, extremely unstable. This paper explain the difference.

Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

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Richard eBeare

2016-03-01

Full Text Available 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 nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

Forest landscape restoration : reconciling biodiversity conservation with local livelihoods in Ecuador

OpenAIRE

Middendorp, Romaike Sanne

2017-01-01

Tropical forest conversion and agricultural intensification are important drivers of loss of biodiversity and ecosystem services on which local communities depend. Resilient agricultural landscapes are crucial to safeguard food security and adapt to environmental and climate changes. An increasing number of policies and programs target forest landscape restoration but lack the scientific basis to ensure sustainable outcomes. This dissertation explores the potential of forest landscape restora...

Situating adaptation: How governance challenges and perceptions of uncertainty influence adaptation in the Rocky Mountains

Science.gov (United States)

Carina Wyborn; Laurie Yung; Daniel Murphy; Daniel R. Williams

2015-01-01

Adaptation is situated within multiple, interacting social, political, and economic forces. Adaptation pathways envision adaptation as a continual pathway of change and response embedded within this broader sociopolitical context. Pathways emphasize that current decisions are both informed by past actions and shape the landscape of future options. This research...

Exploring repetitive DNA landscapes using REPCLASS, a tool that automates the classification of transposable elements in eukaryotic genomes.

Science.gov (United States)

Feschotte, Cédric; Keswani, Umeshkumar; Ranganathan, Nirmal; Guibotsy, Marcel L; Levine, David

2009-07-23

Eukaryotic genomes contain large amount of repetitive DNA, most of which is derived from transposable elements (TEs). Progress has been made to develop computational tools for ab initio identification of repeat families, but there is an urgent need to develop tools to automate the annotation of TEs in genome sequences. Here we introduce REPCLASS, a tool that automates the classification of TE sequences. Using control repeat libraries, we show that the program can classify accurately virtually any known TE types. Combining REPCLASS to ab initio repeat finding in the genomes of Caenorhabditis elegans and Drosophila melanogaster allowed us to recover the contrasting TE landscape characteristic of these species. Unexpectedly, REPCLASS also uncovered several novel TE families in both genomes, augmenting the TE repertoire of these model species. When applied to the genomes of distant Caenorhabditis and Drosophila species, the approach revealed a remarkable conservation of TE composition profile within each genus, despite substantial interspecific covariations in genome size and in the number of TEs and TE families. Lastly, we applied REPCLASS to analyze 10 fungal genomes from a wide taxonomic range, most of which have not been analyzed for TE content previously. The results showed that TE diversity varies widely across the fungi "kingdom" and appears to positively correlate with genome size, in particular for DNA transposons. Together, these data validate REPCLASS as a powerful tool to explore the repetitive DNA landscapes of eukaryotes and to shed light onto the evolutionary forces shaping TE diversity and genome architecture.

Management for adaptation

Science.gov (United States)

John Innes; Linda A. Joyce; Seppo Kellomaki; Bastiaan Louman; Aynslie Ogden; Ian Thompson; Matthew Ayres; Chin Ong; Heru Santoso; Brent Sohngen; Anita Wreford

2009-01-01

This chapter develops a framework to explore examples of adaptation options that could be used to ensure that the ecosystem services provided by forests are maintained under future climates. The services are divided into broad areas within which managers can identify specific management goals for individual forests or landscapes. Adaptation options exist for the major...

Adapting the botanical landscape of Melbourne Gardens (Royal Botanic Gardens Victoria in response to climate change

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Timothy J. Entwisle

2017-12-01

Full Text Available Botanic gardens around the world maintain collections of living plants for science, conservation, education, beauty and more. These collections change over time – in scope and content – but the predicted impacts of climate change will require a more strategic approach to the succession of plant species and their landscapes. Royal Botanic Gardens Victoria has recently published a ‘Landscape Succession Strategy’ for its Melbourne Gardens, a spectacular botanical landscape established in 1846. The strategy recognizes that with 1.6 million visitors each year, responsibility for a heritage-listed landscape and the need to care for a collection of 8500 plant species of conservation and scientific importance, planting and planning must take into account anticipated changes to rainfall and temperature. The trees we plant today must be suitable for the climate of the twenty-second century. Specifically, the Strategy sets out the steps needed over the next twenty years to transition the botanic garden to one resilient to the climate modelled for 2090. The document includes a range of practical measures and achievable (and at times somewhat aspirational targets. Climate analogues will be used to identify places in Australia and elsewhere with conditions today similar to those predicted for Melbourne in 2090, to help select new species for the collection. Modelling of the natural and cultivated distribution of species will be used to help select suitable growth forms to replace existing species of high value or interest. Improved understanding of temperature gradients within the botanic garden, water holding capacity of soils and plant water use behaviour is already resulting in better targeted planting and irrigation. The goal is to retain a similar diversity of species but transition the collection so that by 2036 at least 75% of the species are suitable for the climate in 2090. Over the next few years we hope to provide 100% of irrigation water

Exploring the fitness landscape of poliovirus

Science.gov (United States)

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.

Adaptive Leadership in Digital Transformation

DEFF Research Database (Denmark)

Hansen, Anne Mette; Kræmmergaard, Pernille; Mathiassen, Lars

2012-01-01

Leaders’ ability to quickly adapt IT practices is especially critical in today’s increasingly turbulent environment with frequent changes in the competitive and technological landscape. However, developing such adaptive leadership is a difficult and complex process. Often, underlying assumptions...

Remotely-Sensed Urban Wet-Landscapes AN Indicator of Coupled Effects of Human Impact and Climate Change

Science.gov (United States)

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.

REMOTELY-SENSED URBAN WET-LANDSCAPES: AN INDICATOR OF COUPLED EFFECTS OF HUMAN IMPACT AND CLIMATE CHANGE

Directory of Open Access Journals (Sweden)

W. Ji

2016-06-01

Full Text Available 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.

Ixodid Ticks (Acari, Ixodidae in Urban Landscapes. A review

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Akimov I. А.

2016-04-01

Full Text Available This study presents the results of content analysis of published works on ixodid ticks in urban conditions in order to determine the species diversity, the vectors of research interests at various stages. Information about ticks in the cities up to the 1980s is incidental, to the point of exclusive, after this point there is targeted research in urban landscapes. There are 106 or 15 % of hard ticks of the world fauna registered in the urban territory, 26 species or 3.7 % being the most abundant. Of the urban hard tick species, 23 (88.5 % can attack humans, and 12 species are the most adapted to the urban landscape: Ixodes ricinus, I. persulcatus, Dermacentor reticulatus, D. marginatus, I. pavlovskyi, I. scapularis (dammini, Amblyomma cajennense, Haemaphysalis longicornis, I. hexagonus, Hyalomma marginatum, Am. americanum, and Rhipicephalus sanguineus. It was determined that the most likely causes of the growing number of publications on ixodids urban landscapes are: global accelerating urbanization, the development of recreational areas, the development of green tourism, the growth of the prestige of outdoor recreation, the creation of new, especially of the landscape parks and a tendency to preserve the native landscape in the cities, a significant increase in the density of populations of common species of hard ticks adapted to living in urban environment. The vectors of further work in urban landscapes will be directed to exact planning of monitoring studies of ixodids and associated tick-borne infections.

Hidden Randomness between Fitness Landscapes Limits Reverse Evolution

Science.gov (United States)

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.

An ecological classification system for the central hardwoods region: The Hoosier National Forest

Science.gov (United States)

James E. Van Kley; George R. Parker

1993-01-01

This study, a multifactor ecological classification system, using vegetation, soil characteristics, and physiography, was developed for the landscape of the Hoosier National Forest in Southern Indiana. Measurements of ground flora, saplings, and canopy trees from selected stands older than 80 years were subjected to TWINSPAN classification and DECORANA ordination....

Modeling Relationships between Surface Water Quality and Landscape Metrics Using the Adaptive Neuro-Fuzzy Inference System, A Case Study in Mazandaran Province

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mohsen Mirzayi

2016-03-01

Full Text Available Landscape indices can be used as an approach for predicting water quality changes to monitor non-point source pollution. In the present study, the data collected over the period from 2012 to 2013 from 81 water quality stations along the rivers flowing in Mazandaran Province were analyzed. Upstream boundries were drawn and landscape metrics were extracted for each of the sub-watersheds at class and landscape levels. Principal component analysis was used to single out the relevant water quality parameters and forward linear regression was employed to determine the optimal metrics for the description of each parameter. The first five components were able to describe 96.61% of the variation in water quality in Mazandaran Province. Adaptive Neuro-fuzzy Inference System (ANFIS and multiple linear regression were used to model the relationship between landscape metrics and water quality parameters. The results indicate that multiple regression was able to predict SAR, TDS, pH, NO3‒, and PO43‒ in the test step, with R2 values equal to 0.81, 0.56, 0.73, 0.44. and 0.63, respectively. The corresponding R2 value of ANFIS in the test step were 0.82, 0.79, 0.82, 0.31, and 0.36, respectively. Clearly, ANFIS exhibited a better performance in each case than did the linear regression model. This indicates a nonlinear relationship between the water quality parameters and landscape metrics. Since different land cover/uses have considerable impacts on both the outflow water quality and the available and dissolved pollutants in rivers, the method can be reasonably used for regional planning and environmental impact assessment in development projects in the region.

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

Science.gov (United States)

Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

2018-02-01

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Cooling towers in the landscape

International Nuclear Information System (INIS)

Boernke, F.

1977-01-01

The cooling tower as a large technical construction is one of the most original industrial buildings. It sticks out as an outlandish element in our building landscape, a giant which cannot be compared with the traditional forms of technical buildings. If it is constructed as a reinforced-concrete hyperboloid, its shape goes beyond all limits of building construction. Judgment of these highly individual constructions is only possible by applying a novel standard breaking completely with tradition. This new scale of height and dimension in industrial construction, and in particular the modern cooling tower, requires painstaking care and design and adaptation to the landscape around it. (orig.) [de

Purification effects of five landscape plants on river landscape water

Science.gov (United States)

Ling, Sun; Lei, Zheng; Mao, Qinqing; Ji, Qingxin

2017-12-01

Five species of landscape plants which are scindapsus aureus, water hyacinth, cockscomb, calendula officinalis and salvia splendens were used as experimental materials to study their removal effects on nitrogen, phosphorus, chemical oxygen demand (CODMn) and suspended solids (SS) in urban river water. The results show that the 5 landscape plants have good adaptability and vitality in water body, among them, water hyacinth had the best life signs than the other 4 plants, and its plant height and root length increased significantly. They have certain removal effects on the nitrogen, phosphorus, CODMn (Chemical Oxygen Demand) and SS (Suspended Substance) in the landscape water of Dalong Lake, Xuzhou. Scindapsus aureus, water hyacinth, cockscomb, calendula officinalis and salvia splendens on the removal rate of total nitrogen were 76.69%, 78.57%, 71.42%, 69.64%, 67.86%; the ammonia nitrogen removal rate were 71.06%, 74.28%, 67.85%, 63.02%, 59.81%;the total phosphorus removal rate were 78.70%, 81.48%, 73.15%, 72.22%, 68.52%;the orthophosphate removal rates were 78.37%, 80.77%, 75.96%, 75.96%, 71.15%;the removal rate of CODMn was 52.5%, 55.35%, 46.02%, 45.42%, 44.19%; the removal rate of SS was 81.4%, 86%, 79.1%, 76.7%, 74.42%.The purification effect of 5 kinds of landscape plants of Dalong Lake in Xuzhou City: water hyacinth> scindapsus aureus>cockscomb>calendula officinalis>salvia splendens.

Differential responses of cryptic bat species to the urban landscape.

Science.gov (United States)

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

South African land-cover characteristics database: a synopsis of the landscape

CSIR Research Space (South Africa)

Fairbanks, DHK

2000-02-01

Full Text Available Thematic Mapper(TM) imagery colled from 1994 to 1996, and (3) a stratified post-classification accuracy assessment using a large sample of field data. The resultant database has yielded substantial information to characterize the landscapes of South Africa...

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

Directory of Open Access Journals (Sweden)

Zhixian Yang

2014-01-01

Full Text Available 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.

Eucalyptus as a landscape tree

Science.gov (United States)

W. Douglas Hamilton

1983-01-01

Ninety-two species of Eucalyptus were evaluated at the University of California re- search station in San Jose. The purpose: to find acceptable new street and park trees. Growth rates and horticultural characteristics were noted. Forty-three species were studied in locations statewide to evaluate site adaptation and landscape usefulness; flooded, cold, dry, saline....

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

Science.gov (United States)

Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

2018-01-01

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

A multi-species modelling approach to examine the impact of alternative climate change adaptation strategies on range shifting ability in a fragmented landscape

OpenAIRE

Synes, Nicholas W.; Watts, Kevin; Palmer, Stephen C.F.; Bocedi, Greta; Bartoń, Kamil A.; Osborne, Patrick E.; Travis, Justin M.J.

2015-01-01

An individual-based model of animal dispersal and population dynamics was used to test the effects of different climate change adaptation strategies on species range shifting ability, namely the improvement of existing habitat, restoration of low quality habitat and creation of new habitat. These strategies were implemented on a landscape typical of fragmentation in the United Kingdom using spatial rules to differentiate between the allocation of strategies adjacent to or away from existing h...

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

Science.gov (United States)

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.

Enterprise Potential: Essence, Classification and Types

Directory of Open Access Journals (Sweden)

Turylo Anatolii M.

2014-02-01

Full Text Available The article considers existing approaches to classification of the enterprise potential as an economic notion. It offers own vision of classification of enterprise potential, which meets modern tendencies of enterprise development. Classification ensures a possibility of a wider description and assessment of enterprise potential and also allows identification of its most significant characteristics. Classification of the enterprise potential is developed by different criteria: by functions, by resource support, by ability to adapt, by the level of detection, by the spectrum of taking into account possibilities, by the period of coverage of possibilities and by the level of use. Analysis of components of the enterprise potential allows obtaining a complete and trustworthy assessment of the state of an enterprise. Adaptation potential of an enterprise is based on principles systemacy and dynamism, it characterises possibilities of adjustment of an enterprise to external and internal economic conditions.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models

DEFF Research Database (Denmark)

Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith

2010-01-01

the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature...... field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v......) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME...

Unsupervised Classification Using Immune Algorithm

OpenAIRE

Al-Muallim, M. T.; El-Kouatly, R.

2012-01-01

Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...

Modern landscape processes affecting archaeological sites along the Colorado River corridor downstream of Glen Canyon Dam, Glen Canyon National Recreation Area, Arizona

Science.gov (United States)

East, Amy E.; Sankey, Joel B.; Fairley, Helen C.; Caster, Joshua J.; Kasprak, Alan

2017-08-29

The landscape of the Colorado River through Glen Canyon National Recreation Area formed over many thousands of years and was modified substantially after the completion of Glen Canyon Dam in 1963. Changes to river flow, sediment supply, channel base level, lateral extent of sedimentary terraces, and vegetation in the post-dam era have modified the river-corridor landscape and have altered the effects of geologic processes that continue to shape the landscape and its cultural resources. The Glen Canyon reach of the Colorado River downstream of Glen Canyon Dam hosts many archaeological sites that are prone to erosion in this changing landscape. This study uses field evaluations from 2016 and aerial photographs from 1952, 1973, 1984, and 1996 to characterize changes in potential windblown sand supply and drainage configuration that have occurred over more than six decades at 54 archaeological sites in Glen Canyon and uppermost Marble Canyon. To assess landscape change at these sites, we use two complementary geomorphic classification systems. The first evaluates the potential for aeolian (windblown) transport of river-derived sand from the active river channel to higher elevation archaeological sites. The second identifies whether rills, gullies, or arroyos (that is, overland drainages that erode the ground surface) exist at the archaeological sites as well as the geomorphic surface, and therefore the relative base level, to which those flow paths drain. Results of these assessments are intended to aid in the management of irreplaceable archaeological resources by the National Park Service and stakeholders of the Glen Canyon Dam Adaptive Management Program.

Landscape Architecture in Contemporary Danish Suburban Development

DEFF Research Database (Denmark)

Roden, Tina Maria

2013-01-01

to evaluate and re-think the both loved and criticised suburbia and its incompatibility in relation to the current environmental and climate prospects, these projects suggest that a landscape orientated approach to (sub)urban development can provide more adaptive and flexible frameworks to meet...

On the Evaluation of Outlier Detection and One-Class Classification Methods

DEFF Research Database (Denmark)

Swersky, Lorne; Marques, Henrique O.; Sander, Jörg

2016-01-01

It has been shown that unsupervised outlier detection methods can be adapted to the one-class classification problem. In this paper, we focus on the comparison of oneclass classification algorithms with such adapted unsupervised outlier detection methods, improving on previous comparison studies ...

Classification of Herbaceous Vegetation Using Airborne Hyperspectral Imagery

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Péter Burai

2015-02-01

Full Text Available Alkali landscapes hold an extremely fine-scale mosaic of several vegetation types, thus it seems challenging to separate these classes by remote sensing. Our aim was to test the applicability of different image classification methods of hyperspectral data in this complex situation. To reach the highest classification accuracy, we tested traditional image classifiers (maximum likelihood classifier—MLC, machine learning algorithms (support vector machine—SVM, random forest—RF and feature extraction (minimum noise fraction (MNF-transformation on training datasets of different sizes. Digital images were acquired from an AISA EAGLE II hyperspectral sensor of 128 contiguous bands (400–1000 nm, a spectral sampling of 5 nm bandwidth and a ground pixel size of 1 m. For the classification, we established twenty vegetation classes based on the dominant species, canopy height, and total vegetation cover. Image classification was applied to the original and MNF (minimum noise fraction transformed dataset with various training sample sizes between 10 and 30 pixels. In order to select the optimal number of the transformed features, we applied SVM, RF and MLC classification to 2–15 MNF transformed bands. In the case of the original bands, SVM and RF classifiers provided high accuracy irrespective of the number of the training pixels. We found that SVM and RF produced the best accuracy when using the first nine MNF transformed bands; involving further features did not increase classification accuracy. SVM and RF provided high accuracies with the transformed bands, especially in the case of the aggregated groups. Even MLC provided high accuracy with 30 training pixels (80.78%, but the use of a smaller training dataset (10 training pixels significantly reduced the accuracy of classification (52.56%. Our results suggest that in alkali landscapes, the application of SVM is a feasible solution, as it provided the highest accuracies compared to RF and MLC

Methodological issues in systematic reviews of headache trials: adapting historical diagnostic classifications and outcome measures to present-day standards.

Science.gov (United States)

McCrory, Douglas C; Gray, Rebecca N; Tfelt-Hansen, Peer; Steiner, Timothy J; Taylor, Frederick R

2005-05-01

Recent efforts to make headache diagnostic classification and clinical trial methodology more consistent provide valuable advice to trialists generating new evidence on effectiveness of treatments for headache; however, interpreting older trials that do not conform to new standards remains problematic. Systematic reviewers seeking to utilize historical data can adapt currently recommended diagnostic classification and clinical trial methodological approaches to interpret all available data relative to current standards. In evaluating study populations, systematic reviewers can: (i) use available data to attempt to map study populations to diagnoses in the new International Classification of Headache Disorders; and (ii) stratify analyses based on the extent to which study populations are precisely specified. In evaluating outcome measures, systematic reviewers can: (i) summarize prevention studies using headache frequency, incorporating headache index in a stratified analysis if headache frequency is not available; (ii) summarize acute treatment studies using pain-free response as reported in directly measured headache improvement or headache severity outcomes; and (iii) avoid analysis of recurrence or relapse data not conforming to the sustained pain-free response definition.

Adaptive Regularization of Neural Classifiers

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Larsen, Jan; Hansen, Lars Kai

1997-01-01

We present a regularization scheme which iteratively adapts the regularization parameters by minimizing the validation error. It is suggested to use the adaptive regularization scheme in conjunction with optimal brain damage pruning to optimize the architecture and to avoid overfitting. Furthermo......, we propose an improved neural classification architecture eliminating an inherent redundancy in the widely used SoftMax classification network. Numerical results demonstrate the viability of the method...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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...

Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

Science.gov (United States)

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.

Colonizing Dynamic Alluvial and Coastal Landscapes in the Holocene

Science.gov (United States)

Kidder, T.; Liu, X.; Ervin, K.

2017-12-01

Throughout the Holocene humans have had to adapt to dynamic, rapidly changing alluvial and coastal landscapes. Understanding when people inhabit a given environment is an important starting point for exploring human adaptations, but increasingly we need to consider how, and especially why certain environments are used—or not used— so we can understand the consequences of these human actions. Using four case studies—one from the Yellow River Valley, China, one from coastal Jiangsu, China, one from the Mississippi River Valley (Mississippi, USA) and one from the Mississippi River delta (Louisiana , USA)—we develop a model of how humans at various stages of cultural development colonize new environments. Using archaeological data and ecological modeling we investigate the relationship between the timing of landscape colonization and the ecological richness and predictability of any given environment. As new landscapes emerge and mature humans adopt different strategies for exploiting these novel environments that begins with episodic use and increasingly shifts to stable, long-term habitation. The early phase of landscape colonization appears to be the most significant period because it shapes human environmental practices and sets each culture on a trajectory of socio-cultural development. Thus, human-environment interaction is a critical part of the emergence of cultural patterns that shapes the past, present, and even the future.

Modeling forest harvesting effects on landscape pattern in the Northwest Wisconsin Pine Barrens

Science.gov (United States)

Volker C. Radeloff; David J. Mladenoff; Eric J. Gustafson; Robert M. Scheller; Patrick A. Zollner; Hong S. Heilman; H. Resit Akcakaya

2006-01-01

Forest management shapes landscape patterns, and these patterns often differ significantly from those typical for natural disturbance regimes. This may affect wildlife habitat and other aspects of ecosystem function. Our objective was to examine the effects of different forest management decisions on landscape pattern in a fire adapted ecosystem. We used a factorial...

Technology Trends Analysis Using Patent Landscaping

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Sergey Vsevolodovich Kortov

2017-09-01

Full Text Available The article is devoted to the analysis and the choice of the priorities in technology development and, particularly, to the use of patent landscaping as a tool for the study of technology trends. Currently, patent activity indicators are often used for technology foresight and for competitive intelligence as well. Nevertheless, causal relationship between these indicators, on the one hand, and strategic and tactical decisions in the sphere of technological development on meso- and microeconomic level, on the other hand, are not adequately investigated to solve practical tasks. The goal of the work is to systemize the challenges of technology trends analysis, which could be effectively solved on the base of patent landscape analysis. The article analyses the patent landscaping methodology and tools, as well as their use for evaluating the current competitive environment and technology foresight. The authors formulated the generalized classification for the criteria of promising technologies for a selected region. To assess the compliance of a technology with these criteria, we propose a system of corresponding indicators of patenting activity. Using the proposed methodology, we have analysed the patent landscape to select promising technologies for the Sverdlovsk region. The research confirmed the hypothesis of the patent landscapes performance in evaluating such technology indicators as stages of the life cycle stage, universality (applicability in different industries, pace of worldwide development, innovations and science availability in the region and potential possibilities for scientific collaboration with international research institutions and universities. The results of the research may be useful to the wide audience, including representatives small and medium enterprises, large companies and regional authorities for the tasks concerned with the technology trends analysis and technology strategy design

LCMS landscape change monitoring system—results from an information needs assessment

Science.gov (United States)

Kevin Megown; Brian Schwind; Don Evans; Mark. Finco

2015-01-01

Understanding changes in land use and land cover over space and time provides an important means to evaluate complex interactions between human and biophysical systems, to project future conditions, and to design mitigation and adaptive management strategies. Assessing and monitoring landscape change is evolving into a foundational element of climate change adaptation...

Use of landscape-level river signatures in conservation planning: a South African case study

CSIR Research Space (South Africa)

Roux, D

2002-12-01

Full Text Available ecosystems of this area, a desktop approach, supplemented by aerial and land surveys, was used to devise a new river classification typology. This typology incorporated landscape attributes as surrogates for biodiversity patterns, resulting in defined...

Examining fire-prone forest landscapes as coupled human and natural systems

Science.gov (United States)

Thomas A. Spies; Eric M. White; Jeffrey D. Kline; A. Paige Fisher; Alan Ager; John Bailey; John Bolte; Jennifer Koch; Emily Platt; Christine S. Olsen; Derric Jacobs; Bruce Shindler; Michelle M. Steen-Adams; Roger. Hammer

2014-01-01

Fire-prone landscapes are not well studied as coupled human and natural systems (CHANS) and present many challenges for understanding and promoting adaptive behaviors and institutions. Here, we explore how heterogeneity, feedbacks, and external drivers in this type of natural hazard system can lead to complexity and can limit the development of more adaptive approaches...

Modeling Soil-Landscape Relations in the Sonoran Desert, Arizona, USA

Science.gov (United States)

Regmi, N. R.; Rasmussen, C.

2015-12-01

Digital soil mapping (DSM) techniques that integrate remotely sensed surface topography and reflectance, and map soil-landscape associations have the potential in improve understanding of critical zone evolution and landscape processes. The goal of this study was to understand the soil-geomorphic evolution of Quaternary alluvial and eolian deposits in the Sonoran Desert using a data-driven DSM technique and mapping of soil-landscape relationships. An iterative principal component analysis (iPCA) data reduction routine was developed and implemented for a set of LiDAR elevation- and Landsat ETM+-derived environmental covariates that characterize soil-landscape variability. Principal components that explain more than 95% of the soil-landscape variability were then integrated and classified based on an ISODATA (Iterative Self-Organizing Data) unsupervised technique. The classified map was then segmented based on a region growing algorithm and multi-scale maps of soil-landscape relations were developed, which then compared with maps of major arid-region landforms that can be identified on aerial photographs and satellite images by their distinguishing tone and texture, and in the field by their distinguishing surface and sub-surface soil physical, chemical and biological properties. The approach identified and mapped the soil-landscape variability of alluvial and eolian landscapes, and illustrated the applicability of coupling covariate selection and integration by iPCA, ISODATA classifications of integrated layers, and image segmentation for effective spatial prediction of soil-landscape characteristics. The approach developed here is data-driven, cost- and time-effective, applicable for multi-scale mapping, allows incorporation of wide variety of covariates, and provides accurate quantitative prediction of wide range of soil-landscape attributes that are necessary for hydrologic models, land and ecosystem management decisions, and hazard assessment.

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

Science.gov (United States)

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

Using community archetypes to better understand differential community adaptation to wildfire risk.

Science.gov (United States)

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'. © 2016 The Author(s).

Letting Los Angeles Go: Lessons from Feral Landscapes

Directory of Open Access Journals (Sweden)

Joan Woodward

2004-06-01

Full Text Available Los Angeles is home to numerous feral landscapes: designed gardens no longer receiving intentional care. These are cultivated gardens, usually composed of plants from myriad global climate types, which have been abandoned or neglected and have adapted to native rainfall or unintentional water sources such as broken irrigation systems. They are found in canyons and ridges swept by fire, along rights-of-way where properties were condemned for freeways, in once-glorious neighbourhoods fallen on hard times, and in places where speculation places properties on hold. They are found in all regions and are particularly vivid in Los Angeles, proclaimed as "Lurch City" by Cuff (2000, where disruptive urban convulsions are frequent. These sites are rich with information pertinent to conceivable futures in which supplemental resources and care may not be reliable. This article portrays selected feral landscapes, briefly describes their responses to pervasive urban forces over time, and extracts design attributes to consider when creating future resilient landscapes. Scrutiny of these landscapes' decline and tenacity reveals a telling view of a region's volatility and global context and reminds us to take into account probable neglect when shaping future landscapes.

A framework to assess landscape structural capacity to provide regulating ecosystem services in West Africa.

Science.gov (United States)

Inkoom, Justice Nana; Frank, Susanne; Greve, Klaus; Fürst, Christine

2018-03-01

The Sudanian savanna landscapes of West Africa are amongst the world's most vulnerable areas to climate change impacts. Inappropriate land use and agriculture management practices continuously impede the capacity of agricultural landscapes to provide ecosystem services (ES). Given the absence of practical assessment techniques to evaluate the landscape's capacity to provide regulating ES in this region, the goal of this paper is to propose an integrative assessment framework which combines remote sensing, geographic information systems, expert weighting and landscape metrics-based assessment. We utilized Analytical Hierarchical Process and Likert scale for the expert weighting of landscape capacity. In total, 56 experts from several land use and landscape management related departments participated in the assessment. Further, we adapted the hemeroby concept to define areas of naturalness while landscape metrics including Patch Density, Shannon's Diversity, and Shape Index were utilized for structural assessment. Lastly, we tested the reliability of expert weighting using certainty measurement rated by experts themselves. Our study focused on four regulating ES including flood control, pest and disease control, climate control, and wind erosion control. Our assessment framework was tested on four selected sites in the Vea catchment area of Ghana. The outcome of our study revealed that highly heterogeneous landscapes have a higher capacity to provide pest and disease control, while less heterogeneous landscapes have a higher potential to provide climate control. Further, we could show that the potential capacities to provide ecosystem services are underestimated by 15% if landscape structural aspects assessed through landscape metrics are not considered. We conclude that the combination of adapted land use and an optimized land use pattern could contribute considerably to lower climate change impacts in West African agricultural landscapes. Copyright © 2017 Elsevier

Computerized Classification Testing with the Rasch Model

Science.gov (United States)

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,…

Tool or Toy? Virtual Globes in Landscape Planning

Directory of Open Access Journals (Sweden)

Stephen R. J. Sheppard

2011-10-01

Full Text Available Virtual globes, i.e., geobrowsers that integrate multi-scale and temporal data from various sources and are based on a globe metaphor, have developed into serious tools that practitioners and various stakeholders in landscape and community planning have started using. Although these tools originate from Geographic Information Systems (GIS, they have become a different, potentially interactive and public tool set, with their own specific limitations and new opportunities. Expectations regarding their utility as planning and community engagement tools are high, but are tempered by both technical limitations and ethical issues [1,2]. Two grassroots campaigns and a collaborative visioning process, the Kimberley Climate Adaptation Project case study (British Columbia, illustrate and broaden our understanding of the potential benefits and limitations associated with the use of virtual globes in participatory planning initiatives. Based on observations, questionnaires and in-depth interviews with stakeholders and community members using an interactive 3D model of regional climate change vulnerabilities, potential impacts, and possible adaptation and mitigation scenarios in Kimberley, the benefits and limitations of virtual globes as a tool for participatory landscape planning are discussed. The findings suggest that virtual globes can facilitate access to geospatial information, raise awareness, and provide a more representative virtual landscape than static visualizations. However, landscape is not equally representative at all scales, and not all types of users seem to benefit equally from the tool. The risks of misinterpretation can be managed by integrating the application and interpretation of virtual globes into face-to-face planning processes.

Use of Binary Partition Tree and energy minimization for object-based classification of urban land cover

Science.gov (United States)

Li, Mengmeng; Bijker, Wietske; Stein, Alfred

2015-04-01

Two main challenges are faced when classifying urban land cover from very high resolution satellite images: obtaining an optimal image segmentation and distinguishing buildings from other man-made objects. For optimal segmentation, this work proposes a hierarchical representation of an image by means of a Binary Partition Tree (BPT) and an unsupervised evaluation of image segmentations by energy minimization. For building extraction, we apply fuzzy sets to create a fuzzy landscape of shadows which in turn involves a two-step procedure. The first step is a preliminarily image classification at a fine segmentation level to generate vegetation and shadow information. The second step models the directional relationship between building and shadow objects to extract building information at the optimal segmentation level. We conducted the experiments on two datasets of Pléiades images from Wuhan City, China. To demonstrate its performance, the proposed classification is compared at the optimal segmentation level with Maximum Likelihood Classification and Support Vector Machine classification. The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors. We conclude first that integrating BPT with energy minimization offers an effective means for image segmentation. Second, we conclude that the directional relationship between building and shadow objects represented by a fuzzy landscape is important for building extraction.

Landscape based urban drainage - adapting cities to heavier rain storms. P33.09

DEFF Research Database (Denmark)

Backhaus, A.; Bergman, M.; Birch, Heidi

2009-01-01

Climate changes will lead to more intensive rain events in Northern Europe. This will challenge the capacity of drainage systems in urban areas. Conventional sewer based solutions is reaching its technical and economical limits, and complementing strategies are necessary. The Danish research...... project “Black, Blue and Green –Integrated Infrastructure Planning as Key to Sustainable Urban Water Systems” explores the potentials of local detention and infiltration of rainwater by using the urban landscape. Hydrologists, environmental chemists, landscape architects and urban planners join forces...

A DEFINITION OF AUTHENTICITY CONCEPT IN CONSERVATION OF CULTURAL LANDSCAPES

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Somayeh Fadaei Nezhad

2015-03-01

Full Text Available Cultural landscape can be defined as the result of human interaction with nature over time, which has led to the formation of the many and diverse layers of value. Currently, the UNESCO World Heritage Centre has a unique role among other scientific associations. In recent years, the World Heritage Center has put efforts into developing a framework and measures for evaluation and management of cultural landscapes. Moreover, the concept of authenticity; as the transmitter of values and significance of cultural landscape, is considered as the key component in the process of cultural landscape conservation. A lot of scientific resources have pointed out the importance of authenticity in the process of conserving cultural landscapes. However, the role of authenticity within the domain of conservation of cultural landscapes has received little attention. One of the main reasons can be lack of adaptation between conventional definitions of UNESCO and international documents concerning the authenticity for including the flexible and dynamic structure of cultural landscapes around the world. Therefore, this paper seeks to explore and develop a flexible framework in order to redefine the concept of authenticity in relation to cultural landscapes, which has some overlaps with UNESCO definitions despite its differences. For developing this framework, Iranian-Islamic philosophy of Mollasadra is applied and described with some examples of cultural landscapes in Iran.

Modeling Coupled Landscape Evolution and Soil Organic Carbon Dynamics in Intensively Management Landscapes

Science.gov (United States)

Yan, Q.; Kumar, P.

2017-12-01

Soil is the largest reservoir of carbon in the biosphere but in agricultural areas it is going through rapid erosion due disturbance arising from crop harvest, tillage, and tile drainage. Identifying whether the production of soil organic carbon (SOC) from the crops can compensate for the loss due to erosion is critical to ensure our food security and adapt to climate change. In the U.S. Midwest where large areas of land are intensively managed for agriculture practices, predicting soil quantity and quality are critical for maintaining crop yield and other Critical Zone services. This work focuses on modeling the coupled landscape evolutions soil organic carbon dynamics in agricultural fields. It couples landscape evolution, surface water runoff, organic matter transformation, and soil moisture dynamics to understand organic carbon gain and loss due to natural forcing and farming practices, such as fertilizer application and tillage. A distinctive feature of the model is the coupling of surface ad subsurface processes that predicts both surficial changes and transport along with the vertical transport and dynamics. Our results show that landscape evolution and farming practices play dominant roles in soil organic carbon (SOC) dynamics both above- and below-ground. Contrary to the common assumption that a vertical profile of SOC concentration decreases exponentially with depth, we find that in many situations SOC concentration below-ground could be higher than that at the surface. Tillage plays a complex role in organic matter dynamics. On one hand, tillage would accelerate the erosion rate, on the other hand, it would improve carbon storage by burying surface SOC into below ground. Our model consistently reproduces the observed above- and below-ground patterns of SOC in the field sites of Intensively Managed Landscapes Critical Zone Observatory (IMLCZO). This model bridges the gaps between the landscape evolution, below- and above-ground hydrologic cycle, and

Application of a niche-based model for forest cover classification

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Amici V

2012-05-01

Full Text Available In recent years, a surge of interest in biodiversity conservation have led to the development of new approaches to facilitate ecologically-based conservation policies and management plans. In particular, image classification and predictive distribution modeling applied to forest habitats, constitute a crucial issue as forests constitute the most widespread vegetation type and play a key role for ecosystem functioning. Then, the general purpose of this study is to develop a framework that in the absence of large amounts of field data for large areas may allow to select the most appropriate classification. In some cases, a hard division of classes is required, especially as support to environmental policies; despite this it is necessary to take into account problems which derive from a crisp view of ecological entities being mapped, since habitats are expected to be structurally complex and continuously vary within a landscape. In this paper, a niche model (MaxEnt, generally used to estimate species/habitat distribution, has been applied to classify forest cover in a complex Mediterranean area and to estimate the probability distribution of four forest types, producing continuous maps of forest cover. The use of the obtained models as validation of model for crisp classifications, highlighted that crisp classification, which is being continuously used in landscape research and planning, is not free from drawbacks as it is showing a high degree of inner variability. The modeling approach followed by this study, taking into account the uncertainty proper of the natural ecosystems and the use of environmental variables in land cover classification, may represent an useful approach to making more efficient and effective field inventories and to developing effective forest conservation policies.

Multimedia content classification metrics for content adaptation

OpenAIRE

Fernandes, Rui; Andrade, M.T.

2015-01-01

Multimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the conten...

Multimedia content classification metrics for content adaptation

OpenAIRE

Fernandes, Rui; Andrade, M.T.

2016-01-01

Multimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the conten...

Flowscapes : Infrastructure as landscape, landscape as infrastructure. Graduation Lab Landscape Architecture 2012/2013

NARCIS (Netherlands)

Nijhuis, S.; Jauslin, D.; De Vries, C.

2012-01-01

Flowscapes explores infrastructure as a type of landscape and landscape as a type of infrastructure, and is focused on landscape architectonic design of transportation-, green- and water infrastructures. These landscape infrastructures are considered armatures for urban and rural development. With

The Blurred Line between Form and Process: A Comparison of Stream Channel Classification Frameworks.

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Alan Kasprak

Full Text Available Stream classification provides a means to understand the diversity and distribution of channels and floodplains that occur across a landscape while identifying links between geomorphic form and process. Accordingly, stream classification is frequently employed as a watershed planning, management, and restoration tool. At the same time, there has been intense debate and criticism of particular frameworks, on the grounds that these frameworks classify stream reaches based largely on their physical form, rather than direct measurements of their component hydrogeomorphic processes. Despite this debate surrounding stream classifications, and their ongoing use in watershed management, direct comparisons of channel classification frameworks are rare. Here we implement four stream classification frameworks and explore the degree to which each make inferences about hydrogeomorphic process from channel form within the Middle Fork John Day Basin, a watershed of high conservation interest within the Columbia River Basin, U.S.A. We compare the results of the River Styles Framework, Natural Channel Classification, Rosgen Classification System, and a channel form-based statistical classification at 33 field-monitored sites. We found that the four frameworks consistently classified reach types into similar groups based on each reach or segment's dominant hydrogeomorphic elements. Where classified channel types diverged, differences could be attributed to the (a spatial scale of input data used, (b the requisite metrics and their order in completing a framework's decision tree and/or, (c whether the framework attempts to classify current or historic channel form. Divergence in framework agreement was also observed at reaches where channel planform was decoupled from valley setting. Overall, the relative agreement between frameworks indicates that criticism of individual classifications for their use of form in grouping stream channels may be overstated. These

A practical guide to environmental association analysis in landscape genomics

OpenAIRE

Rellstab Christian; Gugerli Felix; Eckert Andrew J.; Hancock Angela M.; Holderegger Rolf

2015-01-01

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next generation sequencing which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel data sets describing environmental factors have greatly improved and increasingly become pu...

Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation

DEFF Research Database (Denmark)

This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012. The 17 revised full papers presented were carefully reviewed and selected from numerous submissi......This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012. The 17 revised full papers presented were carefully reviewed and selected from numerous...... submissions. The papers cover topics of state of the art contributions, features and classification, location context, language and semantics, music retrieval, and adaption and HCI....

IMPACTS OF PATCH SIZE AND LAND COVER HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

Science.gov (United States)

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,...

Shifting Restoration Policy to Address Landscape Change, Novel Ecosystems, and Monitoring

Directory of Open Access Journals (Sweden)

Joy B. Zedler

2012-12-01

Full Text Available Policy to guide ecological restoration needs to aim toward minimizing the causes of ecosystem degradation; where causes cannot be eliminated or minimized, policy needs to shift toward accommodating irreversible landscape alterations brought about by climate change, nitrogen deposition, altered hydrology, degraded soil, and declining biodiversity. The degree to which lost diversity and ecosystem services can be recovered depends on the extent and nature of landscape change. For wetlands that occur at the base of watersheds that have been developed for agriculture or urban centers, the inflows of excess water, sediment, and nutrients can be permanent and can severely challenge efforts to restore historical services, including biodiversity support. In such cases, the historical state of downstream wetlands will not be completely restorable. Wetland restoration policy should promote watershed planning, wherein wetland and upland restoration is prioritized to achieve multiple, specific ecosystem services. For downstream wetlands, it is realistic to aim to enhance nitrogen removal and to establish native plants that are matrix dominants, namely, those that facilitate rather than displace other natives. More ambitious objectives such as maximizing diversity would be suitable for less-altered, upstream wetlands. Policy should also call for adaptive restoration and long-term assessments. For large sites and multiple sites of a given wetland type within a region, experimental tests can determine a wetland's ability to support high levels of ecosystem services. Once projects are underway, long-term monitoring of structural and functional indicators can characterize progress toward each objective. Managers can then learn which targets are unachievable based on data, not just opinion. Where an experimental treatment shows limited progress, practitioners would shift to more promising treatments and targets, thereby adapting restoration efforts to changing

Pedo-environmental evolution and agricultural landscape transformation

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Gilmo Vianello

Full Text Available Landscapes represent the stage setting of the ecosystem, the great theatre where the evolution of the environment, the changing of things and plant and animal life are played out; the diversity of landscapes derives from the combination, over time, of different environmental factors having perceptibly different roles, as in the case of climate, vegetation and human activity. Less perceptible and scarcely known is the role of soil, which has the ability not only to diversify the ecosystem’s landscapes but also to differentiate its level of productivity and liveability. The role of soil as part of the landscape is not always so evident, especially when it is covered by vegetation that precludes observation. At times, however, soils show themselves conspicuously, at least on the surface, when the colours of the epipedons invade the landscape and – in the ploughing season – dominate it. While it may be reassuring to see neatly cultivated fields and crops growing luxuriantly and homogeneously, the increasingly marked and evident signs of soil degradation or erosion are a cause for concern. In the recent past, the relationship between man and soil resources was strongly influenced by natural factors inside and outside the soil itself, socio-economic conditions and above all the labour force, i.e. the people employed in the primary sector; consequently, it was based on such factors that crop-growing choices were adapted to the different ecosystems, resulting in a diversification of rural landscapes. Starting from the second half of the twentieth century, the introduction of chemicals, mechanisation and exploitation of various forms of energy drastically transformed land use in the space of just a few years, with a logic aimed at improving the production capacity of farmland and forest land in both qualitative and quantitative terms. As a consequence, farming choices that were formerly adapted to the natural and socio-economic conditions of

Pedo-environmental evolution and agricultural landscape transformation

Directory of Open Access Journals (Sweden)

Gilmo Vianello

2009-10-01

Full Text Available Landscapes represent the stage setting of the ecosystem, the great theatre where the evolution of the environment, the changing of things and plant and animal life are played out; the diversity of landscapes derives from the combination, over time, of different environmental factors having perceptibly different roles, as in the case of climate, vegetation and human activity. Less perceptible and scarcely known is the role of soil, which has the ability not only to diversify the ecosystem’s landscapes but also to differentiate its level of productivity and liveability. The role of soil as part of the landscape is not always so evident, especially when it is covered by vegetation that precludes observation. At times, however, soils show themselves conspicuously, at least on the surface, when the colours of the epipedons invade the landscape and – in the ploughing season – dominate it. While it may be reassuring to see neatly cultivated fields and crops growing luxuriantly and homogeneously, the increasingly marked and evident signs of soil degradation or erosion are a cause for concern. In the recent past, the relationship between man and soil resources was strongly influenced by natural factors inside and outside the soil itself, socio-economic conditions and above all the labour force, i.e. the people employed in the primary sector; consequently, it was based on such factors that crop-growing choices were adapted to the different ecosystems, resulting in a diversification of rural landscapes. Starting from the second half of the twentieth century, the introduction of chemicals, mechanisation and exploitation of various forms of energy drastically transformed land use in the space of just a few years, with a logic aimed at improving the production capacity of farmland and forest land in both qualitative and quantitative terms. As a consequence, farming choices that were formerly adapted to the natural and socio-economic conditions of

Adaptation approaches for conserving ecosystems services and biodiversity in dynamic landscapes caused by climate change

Science.gov (United States)

Oswald J. Schmitz; Anne M. Trainor

2014-01-01

Climate change stands to cause animal species to shift their geographic ranges. This will cause ecosystems to become reorganized across landscapes as species migrate into and out of specific locations with attendant impacts on values and services that ecosystems provide to humans. Conservation in an era of climate change needs to ensure that landscapes are resilient by...

Landscape structure affects specialists but not generalists in naturally fragmented grasslands

Science.gov (United States)

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.

Principles for ecological classification

Science.gov (United States)

Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

1999-01-01

The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

The Where-How of Leadership Emergence (WHOLE) Landscape: Charting Emergent Collective Leadership

OpenAIRE

Johnson, Norman; Watkins, Jennifer H

2008-01-01

Leadership resources are constantly adapting to the challenge of the dynamic and complex systems in which they must function. To understand the changing leadership types and to better guide the development of new leadership resources, we propose a two-dimensional leadership landscape that provides a perspective into past leadership resources and identifies new frontiers of leadership. In the Where-How of Leadership Emergence (WHOLE) Landscape, one dimension is where leadership occurs – rangi...

Land Cover Classification in Complex and Fragmented Agricultural Landscapes of the Ethiopian Highlands

Directory of Open Access Journals (Sweden)

Michael Eggen

2016-12-01

Full Text Available Ethiopia is a largely agrarian country with nearly 85% of its employment coming from agriculture. Nevertheless, it is not known how much land is under cultivation. Mapping land cover at finer resolution and global scales has been particularly difficult in Ethiopia. The study area falls in a region of high mapping complexity with environmental challenges which require higher quality maps. Here, remote sensing is used to classify a large area of the central and northwestern highlands into eight broad land cover classes that comprise agriculture, grassland, woodland/shrub, forest, bare ground, urban/impervious surfaces, water, and seasonal water/marsh areas. We use data from Landsat spectral bands from 2000 to 2011, the Normalized Difference Vegetation Index (NDVI and its temporal mean and variance, together with a digital elevation model, all at 30-m spatial resolution, as inputs to a supervised classifier. A Support Vector Machines algorithm (SVM was chosen to deal with the size, variability and non-parametric nature of these data stacks. In post-processing, an image segmentation algorithm with a minimum mapping unit of about 0.5 hectares was used to convert per pixel classification results into an object based final map. Although the reliability of the map is modest, its overall accuracy is 55%—encouraging results for the accuracy of agricultural uses at 85% suggest that these methods do offer great utility. Confusion among grassland, woodland and barren categories reflects the difficulty of classifying savannah landscapes, especially in east central Africa with monsoonal-driven rainfall patterns where the ground is obstructed by clouds for significant periods of time. Our analysis also points out the need for high quality reference data. Further, topographic analysis of the agriculture class suggests there is a significant amount of sloping land under cultivation. These results are important for future research and environmental monitoring in

An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

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Ming Liu

2017-09-01

Full Text Available Algorithms for locomotion mode recognition (LMR based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA, LearnIng From Testing data (LIFT, and Transductive Support Vector Machine (TSVM, were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs.

LANDSCAPE ECOLOGICAL METHOD TO STUDY AGRICULTURAL VEGETATION: SOME EXAMPLES FROM THE PO VALLEY

Directory of Open Access Journals (Sweden)

E. GIGLIO

2006-01-01

Full Text Available Vegetation is the most important landscape component, as regards to its ability to catch solar energy and to transform it, but also to shape the landscape, to structure the space, to create the fit environment for different animal species, to contribute to the maintenance of a correct metastability level for the landscape, etc. It is a biological system which acts under the constraints of the principles of the System Theory and owns the same properties of any other living system: so, it is a complex adaptive, hierarchical, dynamic, dissipative, self-organizing, self-transcendent, autocatalytic, self-maintaining system and follows the non-equilibrium thermodynamic. Its ecological state can be investigated through the comparison between “gathered data” (pathology and “normal data” (physiology for analogous types of vegetation. The Biological Integrated School of Landscape Ecology provides an integrated methodology to define ecological threshold limits of the different Agricultural Landscape types and applies to agricultural vegetation the specific part of the new methodology already tested to studying forests (the Landscape Biological Survey of Vegetation. Ecological quality, better and worst parameters, biological territorial capacity of vegetated corridors, agricultural field, poplar groves, orchards and woody remnant patches are investigated. Some examples from diverse agricultural landscapes of the Po Valley will be discussed. KEY WORDS: agricultural landscape, vegetation, landscape ecology, landscape health, Biological Integrated Landscape Ecology, Landscape Biological Survey of vegetation.

LANDSCAPE ECOLOGICAL METHOD TO STUDY AGRICULTURAL VEGETATION: SOME EXAMPLES FROM THE PO VALLEY

Directory of Open Access Journals (Sweden)

E. GIGLIO

2006-05-01

Full Text Available Vegetation is the most important landscape component, as regards to its ability to catch solar energy and to transform it, but also to shape the landscape, to structure the space, to create the fit environment for different animal species, to contribute to the maintenance of a correct metastability level for the landscape, etc. It is a biological system which acts under the constraints of the principles of the System Theory and owns the same properties of any other living system: so, it is a complex adaptive, hierarchical, dynamic, dissipative, self-organizing, self-transcendent, autocatalytic, self-maintaining system and follows the non-equilibrium thermodynamic. Its ecological state can be investigated through the comparison between “gathered data” (pathology and “normal data” (physiology for analogous types of vegetation. The Biological Integrated School of Landscape Ecology provides an integrated methodology to define ecological threshold limits of the different Agricultural Landscape types and applies to agricultural vegetation the specific part of the new methodology already tested to studying forests (the Landscape Biological Survey of Vegetation. Ecological quality, better and worst parameters, biological territorial capacity of vegetated corridors, agricultural field, poplar groves, orchards and woody remnant patches are investigated. Some examples from diverse agricultural landscapes of the Po Valley will be discussed. KEY WORDS: agricultural landscape, vegetation, landscape ecology, landscape health, Biological Integrated Landscape Ecology, Landscape Biological Survey of vegetation.

Water balances of two Piedmont headwater catchments: implications for regional hydrologic landscape classification

Science.gov (United States)

C. Dreps; G. Sun; J. Boggs

2014-01-01

In the Piedmont of North Carolina, a traditionally water-rich region, reservoirs that serve over 1 million people are under increasing pressure due to naturally occurring droughts and increasing land development. Innovative development approaches aim to maintain hydrologic conditions of the undisturbed landscape, but are based on insufficient target information. This...

Dynamic Gene-Resource Landscape Management of Norway Spruce: Combining Utilization and Conservation

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Milan Lstibůrek

2017-10-01

Full Text Available Traditional gene-resource management programs for forest trees are long-term endeavors requiring sustained organizational commitment covering extensive landscapes. While successful in maintaining adaptation, genetic diversity and capturing traditional growth attributes gains, these programs are dependent on rigid methods requiring elaborate mating schemes, thus making them slow in coping with climate change challenges. Here, we review the significance of Norway spruce in the boreal region and its current management practices. Next, we discuss opportunities offered by novel technologies and, with the use of computer simulations, we propose and evaluate a dynamic landscape gene-resource management in Norway. Our suggested long-term management approach capitalizes on: (1 existing afforestation activities, natural crosses, and DNA-based pedigree assembly to create structured pedigree for evaluation, thus traditional laborious control crosses are avoided and (2 landscape level genetic evaluation, rather than localized traditional progeny trials, allowing for screening of adapted individuals across multiple environmental gradients under changing climate. These advantages lead to greater genetic response to selection in adaptive traits without the traditional breeding and testing scheme, facilitating conservation of genetic resources within the breeding population of the most important forest tree species in Norway. The use of in situ selection from proven material exposed to realistic conditions over vast territories has not been conducted in forestry before. Our proposed approach is in contrast to worldwide current programs, where genetic evaluation is constrained by the range of environments where testing is conducted, which may be insufficient to capture the broad environmental variation necessary to tackle adaptation under changing climate.

The Role of Anthropogenic Modifications in Landscape and Hydrological Organization of Mayma River Basin

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Lubenets Liliya Fedorovna

2015-04-01

Full Text Available The landscape and hydrological organization of the territory is a mosaic of landscapes with different modes of water yield and water balance structure. The landscape and hydrological approach becomes very important under the lack of hydrometeorological information. The factors determining the landscape and hydrological organization of the Mayma river basin, located in the Russian Altai, are considered in the present article. The classification of the landscape and hydrological complexes based on the static and dynamic indicators is performed. The set of interpretive landscape and hydrological maps has been developed. The climatic and hydrological conditions provide the excess moisture over a larger part of the basin. The lithological and hydrological background is characterized by the predominance of rocks and thin weathering products. A peculiarity of the studied area is the prevalence of transit locations that creates risks of dangerous hydrological processes in case of excessive humidity. Using the remote sensing data, the main classes of ground cover are described. A significant anthropogenic impact on the basin landscapes is observed. The analysis of soil structure shows that anthropogenically modified (mostly situated on slopes soils make up approximately 30 %. It is assumed that it leads to the deterioration of the landscape and hydrological situation in the catchment. It is concluded that the landscape and hydrological approach allows solving the problems on minimizing the hydrological objects damage and optimizing the nature management in the catchment in the context of the lack of hydrometeorological information.

Landscape Studio

DEFF Research Database (Denmark)

Hansen, Peter Lundsgaard

2017-01-01

Landscape studio documents is the biography of the method 'design conversation' and contributes to the way we work with landscapes. The blog communicates renewed landscape didactics and leads to the innovation of design practices.......Landscape studio documents is the biography of the method 'design conversation' and contributes to the way we work with landscapes. The blog communicates renewed landscape didactics and leads to the innovation of design practices....

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Temporal and spatial changes of land use and landscape in a coal mining area in Xilingol grassland

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Guan, Chunzhu; Zhang, Baolin; Li, Jiannan; Zhao, Junling

2017-01-01

Coal mining, particularly surface mining, inevitably disturbs land. According to Landsat images acquired over Xilingol grassland in 2005, 2009 and 2015, land uses were divided into seven classes, i. e., open stope, stripping area, waste-dump area, mine industrial area, farmland, urban area and the original landscape (grassland), using supervised classification and human-computer interactive interpretation. The overall classification accuracies were 97.72 %, 98.43 % and 96.73 %, respectively; the Kappa coefficients were 0.95, 0.97 and 0.95, respectively. Analysis on LUCC (Land Use and Cover Change) showed that surface coal mining disturbed grassland ecosystem: grassland decreased by 8661.15 hm2 in 2005-2015. The area and proportion of mining operation areas (open stope, stripping area, waste-dump area, mine industrial field) increased, but those of grassland decreased continuously. Transfer matrix of land use changes showed that waste-dump had the largest impacts in mining disturbance, and that effective reclamation of waste-dump areas would mitigate eco-environment destruction, as would be of great significance to protect fragile grassland eco-system. Six landscape index showed that landscape fragmentation increased, and the influences of human activity on landscape was mainly reflected in the expansion of mining area and urban area. Remote sensing monitoring of coal surface mining in grassland would accurately demonstrate the dynamics and trend of LUCC, providing scientific supports for ecological reconstruction in surface mining area.

The interpretations and uses of fitness landscapes in the social sciences

NARCIS (Netherlands)

L.M. Gerrits (Lasse); P.K. Marks (Peter)

2014-01-01

markdownabstract__Abstract__ This working paper precedes our full article entitled “The evolution of Wright’s (1932) adaptive field to contemporary interpretations and uses of fitness landscapes in the social sciences” as published in the journal Biology & Philosophy

The impact of weight classification on safety: timing steps to adapt to external constraints

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Gill, S.V.

2015-01-01

Objectives: The purpose of the current study was to evaluate how weight classification influences safety by examining adults’ ability to meet a timing constraint: walking to the pace of an audio metronome. Methods: With a cross-sectional design, walking parameters were collected as 55 adults with normal (n=30) and overweight (n=25) body mass index scores walked to slow, normal, and fast audio metronome paces. Results: Between group comparisons showed that at the fast pace, those with overweight body mass index (BMI) had longer double limb support and stance times and slower cadences than the normal weight group (all psmetronome paces revealed that participants who were overweight had higher cadences at the slow and fast paces (all ps<0.05). Conclusions: Findings suggest that those with overweight BMI alter their gait to maintain biomechanical stability. Understanding how excess weight influences gait adaptation can inform interventions to improve safety for individuals with obesity. PMID:25730658

Post-industrial landscapes in the Czech Republic - A GIS assisted search for present state

Czech Academy of Sciences Publication Activity Database

Kolejka, Jaromír; Klimánek, M.

2012-01-01

Roč. 6, č. 2 (2012), s. 7-16 ISSN 1843-5920 R&D Projects: GA AV ČR IAA300860903 Keywords : post-industrial landscape * identification criteria * GIS classification and typology * territorial distribution Subject RIV: DE - Earth Magnetism, Geodesy, Geography http://geographianapocensis.acad-cluj.ro/Revista/Revista_eng/index.htm

Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification.

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Li, Jinyan; Fong, Simon; Sung, Yunsick; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2016-01-01

An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating class are rare in a population, such as medical anomalies, positive clinical tests, and particular diseases. Although the target samples in the primitive dataset are small in number, the induction of a classification model over such training data leads to poor prediction performance due to insufficient training from the minority class. In this paper, we use a novel class-balancing method named adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique (ASCB_DmSMOTE) to solve this imbalanced dataset problem, which is common in biomedical applications. The proposed method combines under-sampling and over-sampling into a swarm optimisation algorithm. It adaptively selects suitable parameters for the rebalancing algorithm to find the best solution. Compared with the other versions of the SMOTE algorithm, significant improvements, which include higher accuracy and credibility, are observed with ASCB_DmSMOTE. Our proposed method tactfully combines two rebalancing techniques together. It reasonably re-allocates the majority class in the details and dynamically optimises the two parameters of SMOTE to synthesise a reasonable scale of minority class for each clustered sub-imbalanced dataset. The proposed methods ultimately overcome other conventional methods and attains higher credibility with even greater accuracy of the classification model.

Dynamics of a temperate deciduous forest under landscape-scale management: Implications for adaptability to climate change

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Matthew G. Olson; Benjamin O. Knapp; John M. Kabrick

2017-01-01

Landscape forest management is an approach to meeting diverse objectives that collectively span multiple spatial scales. It is critical that we understand the long-term effects of landscape management on the structure and composition of forest tree communities to ensure that these practices are sustainable. Furthermore, it is increasingly important to also consider...

Adaptive Automation Design and Implementation

Science.gov (United States)

2015-09-17

with an automated system to a real-world adaptive au- tomation system implementation. There have been plenty of adaptive automation 17 Adaptive...of systems without increasing manpower requirements by allocating routine tasks to automated aids, improving safety through the use of au- tomated ...between intermediate levels of au- tomation , explicitly defining which human task a given level automates. Each model aids the creation and classification

Adaptive evolution of plastron shape in emydine turtles.

Science.gov (United States)

Angielczyk, Kenneth D; Feldman, Chris R; Miller, Gretchen R

2011-02-01

Morphology reflects ecological pressures, phylogeny, and genetic and biophysical constraints. Disentangling their influence is fundamental to understanding selection and trait evolution. Here, we assess the contributions of function, phylogeny, and habitat to patterns of plastron (ventral shell) shape variation in emydine turtles. We quantify shape variation using geometric morphometrics, and determine the influence of several variables on shape using path analysis. Factors influencing plastron shape variation are similar between emydine turtles and the more inclusive Testudinoidea. We evaluate the fit of various evolutionary models to the shape data to investigate the selective landscape responsible for the observed morphological patterns. The presence of a hinge on the plastron accounts for most morphological variance, but phylogeny and habitat also correlate with shape. The distribution of shape variance across emydine phylogeny is most consistent with an evolutionary model containing two adaptive zones--one for turtles with kinetic plastra, and one for turtles with rigid plastra. Models with more complex adaptive landscapes often fit the data only as well as the null model (purely stochastic evolution). The adaptive landscape of plastron shape in Emydinae may be relatively simple because plastral kinesis imposes overriding mechanical constraints on the evolution of form. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

GEOSPATIAL ANALYSIS OF ATMOSPHERIC HAZE EFFECT BY SOURCE AND SINK LANDSCAPE

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T. Yu

2017-09-01

Full Text Available Based on geospatial analysis model, this paper analyzes the relationship between the landscape patterns of source and sink in urban areas and atmospheric haze pollution. Firstly, the classification result and aerosol optical thickness (AOD of Wuhan are divided into a number of square grids with the side length of 6 km, and the category level landscape indices (PLAND, PD, COHESION, LPI, FRAC_MN and AOD of each grid are calculated. Then the source and sink landscapes of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. Next, to make the following analysis more efficient, the indices selected before should be determined through the correlation coefficient between them. Finally, due to the spatial dependency and spatial heterogeneity of the data used in this paper, spatial autoregressive model and geo-weighted regression model are used to analyze atmospheric haze effect by source and sink landscape from the global and local level. The results show that the source landscape of atmospheric haze pollution is the building, and the sink landscapes are shrub and woodland. PLAND, PD and COHESION are suitable for describing the atmospheric haze effect by source and sink landscape. Comparing these models, the fitting effect of SLM, SEM and GWR is significantly better than that of OLS model. The SLM model is superior to the SEM model in this paper. Although the fitting effect of GWR model is more unsuited than that of SLM, the influence degree of influencing factors on atmospheric haze of different geography can be expressed clearer. Through the analysis results of these models, following conclusions can be summarized: Reducing the proportion of source landscape area and increasing the degree of fragmentation could cut down aerosol optical thickness; And distributing the source and sink landscape evenly and interspersedly could effectively reduce aerosol optical thickness which represents

Geospatial Analysis of Atmospheric Haze Effect by Source and Sink Landscape

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Yu, T.; Xu, K.; Yuan, Z.

2017-09-01

Based on geospatial analysis model, this paper analyzes the relationship between the landscape patterns of source and sink in urban areas and atmospheric haze pollution. Firstly, the classification result and aerosol optical thickness (AOD) of Wuhan are divided into a number of square grids with the side length of 6 km, and the category level landscape indices (PLAND, PD, COHESION, LPI, FRAC_MN) and AOD of each grid are calculated. Then the source and sink landscapes of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. Next, to make the following analysis more efficient, the indices selected before should be determined through the correlation coefficient between them. Finally, due to the spatial dependency and spatial heterogeneity of the data used in this paper, spatial autoregressive model and geo-weighted regression model are used to analyze atmospheric haze effect by source and sink landscape from the global and local level. The results show that the source landscape of atmospheric haze pollution is the building, and the sink landscapes are shrub and woodland. PLAND, PD and COHESION are suitable for describing the atmospheric haze effect by source and sink landscape. Comparing these models, the fitting effect of SLM, SEM and GWR is significantly better than that of OLS model. The SLM model is superior to the SEM model in this paper. Although the fitting effect of GWR model is more unsuited than that of SLM, the influence degree of influencing factors on atmospheric haze of different geography can be expressed clearer. Through the analysis results of these models, following conclusions can be summarized: Reducing the proportion of source landscape area and increasing the degree of fragmentation could cut down aerosol optical thickness; And distributing the source and sink landscape evenly and interspersedly could effectively reduce aerosol optical thickness which represents atmospheric haze

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

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Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

Physical-geographical landscape of the tourist circuit Chilpancingo-Azul, Guerrero State, Mexico

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Julio C. Carbajal Monroy

2011-02-01

Full Text Available This work deals with the delimitation of physical-geographical landscapes of the territory of the Tourist Circuit Chilpancingo Azul, at Guerrero's State central region, from geo-ecological conception for the physical-geographical synthetic classification of territorial units. This approach obtained territorial units and its hierarchical classification using a taxonomic system of localities, neighborhoods and boroughs (smallest categories. Taking into account the 1:100 000 scale different geographical units were determined: 3 localities, 31 neighborhoods and 177 boroughs. The characterization of these territorial units include lithologic constitution, geomorphological conditions (morphogenesis and morphometrics and spatial distribution of major types of soils and vegetation and land uses in the territory.

Algorithms for adaptive nonlinear pattern recognition

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Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary

2011-09-01

In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral

Czech Post-industrial Landscapes in the Border Zone with Austria: Identification, Typology nad Value

Czech Academy of Sciences Publication Activity Database

Kolejka, Jaromír; Klimánek, M.; Hrádek, Mojmír; Kirchner, Karel

2017-01-01

Roč. 159, č. 159 (2017), s. 221-242 ISSN 0029-9138 R&D Projects: GA AV ČR IAA300860903 Institutional support: RVO:68145535 Keywords : post-industrial landscape * mapping * GIS * border zone with Austria * classification Subject RIV: DE - Earth Magnetism, Geodesy, Geography OBOR OECD: Physical geography Impact factor: 0.167, year: 2016

Social learning solves the problem of narrow-peaked search landscapes: experimental evidence in humans.

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Acerbi, Alberto; Tennie, Claudio; Mesoudi, Alex

2016-09-01

The extensive use of social learning is considered a major reason for the ecological success of humans. Theoretical considerations, models and experiments have explored the evolutionary basis of social learning, showing the conditions under which learning from others is more adaptive than individual learning. Here we present an extension of a previous experimental set-up, in which individuals go on simulated 'hunts' and their success depends on the features of a 'virtual arrowhead' they design. Individuals can modify their arrowhead either by individual trial and error or by copying others. We study how, in a multimodal adaptive landscape, the smoothness of the peaks influences learning. We compare narrow peaks, in which solutions close to optima do not provide useful feedback to individuals, to wide peaks, where smooth landscapes allow an effective hill-climbing individual learning strategy. We show that individual learning is more difficult in narrow-peaked landscapes, but that social learners perform almost equally well in both narrow- and wide-peaked search spaces. There was a weak trend for more copying in the narrow than wide condition, although as in previous experiments social information was generally underutilized. Our results highlight the importance of tasks' design space when studying the adaptiveness of high-fidelity social learning.

Disturbances catalyze the adaptation of forest ecosystems to changing climate conditions.

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Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-01-01

The rates of anthropogenic climate change substantially exceed those at which forest ecosystems - dominated by immobile, long-lived organisms - are able to adapt. The resulting maladaptation of forests has potentially detrimental effects on ecosystem functioning. Furthermore, as many forest-dwelling species are highly dependent on the prevailing tree species, a delayed response of the latter to a changing climate can contribute to an extinction debt and mask climate-induced biodiversity loss. However, climate change will likely also intensify forest disturbances. Here, we tested the hypothesis that disturbances foster the reorganization of ecosystems and catalyze the adaptation of forest composition to climate change. Our specific objectives were (i) to quantify the rate of autonomous forest adaptation to climate change, (ii) examine the role of disturbance in the adaptation process, and (iii) investigate spatial differences in climate-induced species turnover in an unmanaged mountain forest landscape (Kalkalpen National Park, Austria). Simulations with a process-based forest landscape model were performed for 36 unique combinations of climate and disturbance scenarios over 1000 years. We found that climate change strongly favored European beech and oak species (currently prevailing in mid- to low-elevation areas), with novel species associations emerging on the landscape. Yet, it took between 357 and 706 years before the landscape attained a dynamic equilibrium with the climate system. Disturbances generally catalyzed adaptation and decreased the time needed to attain equilibrium by up to 211 years. However, while increasing disturbance frequency and severity accelerated adaptation, increasing disturbance size had the opposite effect. Spatial analyses suggest that particularly the lowest and highest elevation areas will be hotspots of future species change. We conclude that the growing maladaptation of forests to climate and the long lead times of autonomous

Design and implementation based on the classification protection vulnerability scanning system

International Nuclear Information System (INIS)

Wang Chao; Lu Zhigang; Liu Baoxu

2010-01-01

With the application and spread of the classification protection, Network Security Vulnerability Scanning should consider the efficiency and the function expansion. It proposes a kind of a system vulnerability from classification protection, and elaborates the design and implementation of a vulnerability scanning system based on vulnerability classification plug-in technology and oriented classification protection. According to the experiment, the application of classification protection has good adaptability and salability with the system, and it also approves the efficiency of scanning. (authors)

THE PRELIMINARY STUDY ON LANDSCAPE CULTURE ORIENTATION AND EXPLOITATION OF THE SOUTH DONGTING LAKE WETLAND

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

Dongting Lake is internationally an important wetland. We studied and summarized the conception, function, classification and current situation of the wetland-landscape culture in this region. The results showed that the culture of Dongting Lake wetland was rich in diversity, which are the Rice Cultivation Culture, high-balustrade dwelling,Nuo Culture, Ship Culture, Dragon Boat Culture, Chu Culture, Ancient Architecture Landscape, Wetland Foodstuff andCuisine Culture, Civil Art, Historic Heritage and Cultural Relics, Revolutionary Sites and Ruins, and Production andLiving Culture, etc. We also evaluated the eeo-tourism value of wetland landscape culture, and analyzed its features andorientation. The results revealed that the south Dongting Lake wetland plays a key role on the Changjiang(Yangtze) Riverreaches civilization and Chinese civilization, even has great influence on the global civilization. We summarized that thesoul of the south Dongting Lake Culture was Wetland Culture, Water Culture, Rice Cultivation and Chu Culture. Thethoughts, principles and approaches of sustainable exploitation and utilization of the wetland landscape culture were formulated and suggested.

Landscape Ecology

DEFF Research Database (Denmark)

Christensen, Andreas Aagaard; Brandt, Jesper; Svenningsen, Stig Roar

2017-01-01

Landscape ecology is an interdisciplinary field of research and practice that deals with the mutual association between the spatial configuration and ecological functioning of landscapes, exploring and describing processes involved in the differentiation of spaces within landscapes......, and the ecological significance of the patterns which are generated by such processes. In landscape ecology, perspectives drawn from existing academic disciplines are integrated based on a common, spatially explicit mode of analysis developed from classical holistic geography, emphasizing spatial and landscape...... pattern analysis and ecological interaction of land units. The landscape is seen as a holon: an assemblage of interrelated phenomena, both cultural and biophysical, that together form a complex whole. Enduring challenges to landscape ecology include the need to develop a systematic approach able...

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

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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

European landscape architecture and territorial strategies for water landscapes

DEFF Research Database (Denmark)

Diedrich, Lisa Babette

2010-01-01

This article sums up the author’s lecture at the 2009 Sydney Resilient Water Landscapes Symposium and presents a series of realized or planned European landscape architectural and urbanistic projects on water landscapes taken from the recently published book On Site/ Landscape Architecture Europe...... and accompanying reflections. The hypothesis is that further scientific research can help defining weaknesses and strengths of the existing water landscape designs in terms of resilience, extract principles and tools, improve the weak ones and communicate the strong ones and develop general quality criteria...... and tools for future resilient water landscapes....

Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

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István A Kovács

Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

Integration Research for Shaping Sustainable Regional Landscapes

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David J. Brunckhorst

2005-01-01

Full Text Available Ecological and social systems are complex and entwined. Complex social-ecological systems interact in a multitude of ways at many spatial scales across time. Their interactions can contribute both positive and negative consequences in terms of sustainability and the context in which they exist affecting future landscape change. Non-metropolitan landscapes are the major theatre of interactions where large-scale alteration occurs precipitated by local to global forces of economic, social, and environmental change. Such regional landscape effects are critical also to local natural resource and social sustainability. The institutions contributing pressures and responses consequently shape future landscapes and in turn influence how social systems, resource users, governments, and policy makers perceive those landscapes and their future. Science and policy for “sustainable” futures need to be integrated at the applied “on-ground” level where products and effects of system interactions are fully included, even if unobserved. Government agencies and funding bodies often consider such research as “high-risk.” This paper provides some examples of interdisciplinary research that has provided a level of holistic integration through close engagement with landholders and communities or through deliberately implementing integrative and innovative on-ground experimental models. In retrospect, such projects have to some degree integrated through spatial (if not temporal synthesis, policy analysis, and (new or changed institutional arrangements that are relevant locally and acceptable in business, as well as at broader levels of government and geography. This has provided transferable outcomes that can contribute real options and adaptive capacity for suitable positive futures.

DOA Estimation of Low Altitude Target Based on Adaptive Step Glowworm Swarm Optimization-multiple Signal Classification Algorithm

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Zhou Hao

2015-06-01

Full Text Available The traditional MUltiple SIgnal Classification (MUSIC algorithm requires significant computational effort and can not be employed for the Direction Of Arrival (DOA estimation of targets in a low-altitude multipath environment. As such, a novel MUSIC approach is proposed on the basis of the algorithm of Adaptive Step Glowworm Swarm Optimization (ASGSO. The virtual spatial smoothing of the matrix formed by each snapshot is used to realize the decorrelation of the multipath signal and the establishment of a fullorder correlation matrix. ASGSO optimizes the function and estimates the elevation of the target. The simulation results suggest that the proposed method can overcome the low altitude multipath effect and estimate the DOA of target readily and precisely without radar effective aperture loss.

Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird.

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Khimoun, Aurélie; Peterman, William; Eraud, Cyril; Faivre, Bruno; Navarro, Nicolas; Garnier, Stéphane

2017-10-01

Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest specialist bird species, we optimized resistance surfaces without a priori specification, using least-cost (LCP) or resistance (IBR) distances. We implemented a two-step procedure in order (i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then (ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small-scale reduction of gene flow mainly driven by land cover, with a negative impact of the nonforest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting suboptimal movements across this human-modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces. © 2017 John Wiley & Sons Ltd.

LiDAR and Orthophoto Synergy to optimize Object-Based Landscape Change: Analysis of an Active Landslide

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Martijn Kamps

2017-08-01

Full Text Available Active landslides have three major effects on landscapes: (1 land cover change, (2 topographical change, and (3 above ground biomass change. Data derived from multi-temporal Light Detection and Ranging technology (LiDAR are used in combination with multi-temporal orthophotos to quantify these changes between 2006 and 2012, caused by an active deep-seated landslide near the village of Doren in Austria. Land-cover is classified by applying membership-based classification and contextual improvements based on the synergy of orthophotos and LiDAR-based elevation data. Topographical change is calculated by differencing of LiDAR derived digital terrain models. The above ground biomass is quantified by applying a local-maximum algorithm for tree top detection, in combination with allometric equations. The land cover classification accuracies were improved from 65% (using only LiDAR and 76% (using only orthophotos to 90% (using data synergy for 2006. A similar increase from respectively 64% and 75% to 91% was established for 2012. The increased accuracies demonstrate the effectiveness of using data synergy of LiDAR and orthophotos using object-based image analysis to quantify landscape changes, caused by an active landslide. The method has great potential to be transferred to larger areas for use in landscape change analyses.

Inhabiting the Delta: A Landscape Approach to Transformative Socio-Ecological Restoration

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Brett Milligan

2017-09-01

Full Text Available doi: https://doi.org/10.15447/sfews.2017v15iss3art3Current legislation and plans for the Sacramento–San Joaquin Delta (Delta call for large-scale restoration of aquatic and terrestrial habitats, which will require significant changes in waterways, land uses, and cultural patterns. These re-made landscapes will be subject to a variety of new human uses, which Delta planning and adaptive management literature has yet to adequately consider. Failing to account for human uses and evolving place values can lead to diminished performance and public support for Delta restoration efforts. Our empirical study examined restored and naturalized Delta landscapes using an integrative landscape approach that seeks to reconcile multiple goals and land-use agendas that span ecological, social, economic, and political domains. The research design consisted of six overlapping methods that included a planning, policy, and law review specific to the Delta; surveys and interviews with approximately 100 land managers, scientists, land-owners, law-enforcement personnel, agency representatives, and Delta residents; nine case studies of restored and naturalized delta landscapes; GIS mapping; and extensive field work. Findings derived from the synthesis of these methods show that human uses of the Delta’s re-wilded landscapes are diverse and pervasive. Given the infrastructural and urbanized context of the region, these environments are subject to multiple and sometimes conflicting uses, perceptions, and place values. Though these myriad uses cannot be fully predicted or controlled (nor should they be, findings showed that more proactive and inclusive planning for human uses can encourage or discourage particular uses while also building constituency, support, and active engagement in ecological restoration efforts. We conclude that reconciling human uses with ecological recovery in the Delta will require a more localized, multi-functional, and creative approach to

Modified DCTNet for audio signals classification

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Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Optimization of landscape services under uncoordinated management by multiple landowners.

Science.gov (United States)

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.

CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

Directory of Open Access Journals (Sweden)

Yu. B. Popova

2016-01-01

Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

Prediction Reweighting for Domain Adaptation.

Science.gov (United States)

Shuang Li; Shiji Song; Gao Huang

2017-07-01

There are plenty of classification methods that perform well when training and testing data are drawn from the same distribution. However, in real applications, this condition may be violated, which causes degradation of classification accuracy. Domain adaptation is an effective approach to address this problem. In this paper, we propose a general domain adaptation framework from the perspective of prediction reweighting, from which a novel approach is derived. Different from the major domain adaptation methods, our idea is to reweight predictions of the training classifier on testing data according to their signed distance to the domain separator, which is a classifier that distinguishes training data (from source domain) and testing data (from target domain). We then propagate the labels of target instances with larger weights to ones with smaller weights by introducing a manifold regularization method. It can be proved that our reweighting scheme effectively brings the source and target domains closer to each other in an appropriate sense, such that classification in target domain becomes easier. The proposed method can be implemented efficiently by a simple two-stage algorithm, and the target classifier has a closed-form solution. The effectiveness of our approach is verified by the experiments on artificial datasets and two standard benchmarks, a visual object recognition task and a cross-domain sentiment analysis of text. Experimental results demonstrate that our method is competitive with the state-of-the-art domain adaptation algorithms.

Emotions Classification for Arabic Tweets

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... learning methods for referring to all areas of detecting, analyzing, and classifying ... In this paper, an adaptive model is proposed for emotions classification of ... WEKA data mining tool is used to implement this model and evaluate the ... defined using vector representation, storing a numerical. "importance" ...

The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery

Science.gov (United States)

Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya

2018-04-01

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.

Between Efficiency and Resilience: The Classification of Companies According to their Sustainability Performance

OpenAIRE

Nagel, Sebastian; Hiss, Stefanie; Woschnack, Daniela; Teufel, Bernd

2017-01-01

In this article, we provide a broad picture of the adaptation of economic classification technologies that were originally used to provide financial information and to classify companies according to their financial performance. The same approach is now available for the benefit of sustainability investors. The adaptation of such financial classification technologies to account for questions of sustainability has been engendered by the growing importance of financial markets and by the recogn...

Predicting landscape vegetation dynamics using state-and-transition simulation models

Science.gov (United States)

Colin J. Daniel; Leonardo. Frid

2012-01-01

This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

Driving the Landscape

Science.gov (United States)

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.

Raiders of the lost bark: orangutan foraging strategies in a degraded landscape.

Directory of Open Access Journals (Sweden)

Gail Campbell-Smith

Full Text Available Deforestation is rapidly transforming primary forests across the tropics into human-dominated landscapes. Consequently, conservationists need to understand how different taxa respond and adapt to these changes in order to develop appropriate management strategies. Our two year study seeks to determine how wild Sumatran orangutans (Pongo abelii adapt to living in an isolated agroforest landscape by investigating the sex of crop-raiders related to population demographics, and their temporal variations in feeding behaviour and dietary composition. From focal animal sampling we found that nine identified females raided cultivated fruits more than the four males. Seasonal adaptations were shown through orangutan feeding habits that shifted from being predominantly fruit-based (56% of the total feeding time, then 22% on bark to the fallback food of bark (44%, then 35% on fruits, when key cultivated resources such as jackfruit (Artocarpus integer, were unavailable. Cultivated fruits were mostly consumed in the afternoon and evening, when farmers had returned home. The finding that females take greater crop-raiding risks than males differs from previous human-primate conflict studies, probably because of the low risks associated (as farmers rarely retaliated and low intraspecific competition between males. Thus, the behavioral ecology of orangutans living in this human-dominated landscape differs markedly from that in primary forest, where orangutans have a strictly wild food diet, even where primary rainforests directly borders farmland. The importance of wild food availability was clearly illustrated in this study with 21% of the total orangutan feeding time being allocated to feeding on cultivated fruits. As forests are increasingly converted to cultivation, humans and orangutans are predicted to come into conflict more frequently. This study reveals orangutan adaptations for coexisting with humans, e.g. changes in temporal foraging patterns, which

Neighbourhood-scale urban forest ecosystem classification.

Science.gov (United States)

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multifunctional energy landscape for a DNA G-quadruplex: An evolved molecular switch

Science.gov (United States)

Cragnolini, Tristan; Chakraborty, Debayan; Šponer, Jiří; Derreumaux, Philippe; Pasquali, Samuela; Wales, David J.

2017-10-01

We explore the energy landscape for a four-fold telomere repeat, obtaining interconversion pathways between six experimentally characterised G-quadruplex topologies. The results reveal a multi-funnel system, with a variety of intermediate configurations and misfolded states. This organisation is identified with the intrinsically multi-functional nature of the system, suggesting a new paradigm for the classification of such biomolecules and clarifying issues regarding apparently conflicting experimental results.

RS- and GIS-based study on landscape pattern change in the Poyang Lake wetland area, China

Science.gov (United States)

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

Beyond the edge: Linking agricultural landscapes, stream networks, and best management practices

Science.gov (United States)

Kreiling, Rebecca M.; Thoms, Martin C.; Richardson, William B.

2018-01-01

Despite much research and investment into understanding and managing nutrients across agricultural landscapes, nutrient runoff to freshwater ecosystems is still a major concern. We argue there is currently a disconnect between the management of watershed surfaces (agricultural landscape) and river networks (riverine landscape). These landscapes are commonly managed separately, but there is limited cohesiveness between agricultural landscape-focused research and river science, despite similar end goals. Interdisciplinary research into stream networks that drain agricultural landscapes is expanding but is fraught with problems. Conceptual frameworks are useful tools to order phenomena, reveal patterns and processes, and in interdisciplinary river science, enable the joining of multiple areas of understanding into a single conceptual–empirical structure. We present a framework for the interdisciplinary study and management of agricultural and riverine landscapes. The framework includes components of an ecosystems approach to the study of catchment–stream networks, resilience thinking, and strategic adaptive management. Application of the framework is illustrated through a study of the Fox Basin in Wisconsin, USA. To fully realize the goal of nutrient reduction in the basin, we suggest that greater emphasis is needed on where best management practices (BMPs) are used within the spatial context of the combined watershed–stream network system, including BMPs within the river channel. Targeted placement of BMPs throughout the riverine landscape would increase the overall buffering capacity of the system to nutrient runoff and thus its resilience to current and future disturbances.

Geomorpho-Landscapes

Science.gov (United States)

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

Rapid Adaptation in Digital Transformation

DEFF Research Database (Denmark)

Hansen, Anne Mette; Kræmmergaard, Pernille; Mathiassen, Lars

2011-01-01

landscape. In this article, we share insights gained from two public sector organizations in which IS and business leaders used the Participatory Process Model (PPM) designed by the authors to share their assumptions about IS leadership, challenge existing IT strategies and collaboration patterns and adapt...... the organization’s digitization approach. We demonstrate in detail how the leaders within these two organizations were engaged and offer recommendations for how other organizations can use the PPM to rapidly adapt their approaches to digital transformation through more effective IS leadership roles....

KNN BASED CLASSIFICATION OF DIGITAL MODULATED SIGNALS

Directory of Open Access Journals (Sweden)

Sajjad Ahmed Ghauri

2016-11-01

Full Text Available Demodulation process without the knowledge of modulation scheme requires Automatic Modulation Classification (AMC. When receiver has limited information about received signal then AMC become essential process. AMC finds important place in the field many civil and military fields such as modern electronic warfare, interfering source recognition, frequency management, link adaptation etc. In this paper we explore the use of K-nearest neighbor (KNN for modulation classification with different distance measurement methods. Five modulation schemes are used for classification purpose which is Binary Phase Shift Keying (BPSK, Quadrature Phase Shift Keying (QPSK, Quadrature Amplitude Modulation (QAM, 16-QAM and 64-QAM. Higher order cummulants (HOC are used as an input feature set to the classifier. Simulation results shows that proposed classification method provides better results for the considered modulation formats.

Scale Mismatches in Management of Urban Landscapes

Directory of Open Access Journals (Sweden)

Sara T. Borgström

2006-12-01

Full Text Available Urban landscapes constitute the future environment for most of the world's human population. An increased understanding of the urbanization process and of the effects of urbanization at multiple scales is, therefore, key to ensuring human well-being. In many conventional natural resource management regimes, incomplete knowledge of ecosystem dynamics and institutional constraints often leads to institutional management frameworks that do not match the scale of ecological patterns and processes. In this paper, we argue that scale mismatches are particularly pronounced in urban landscapes. Urban green spaces provide numerous important ecosystem services to urban citizens, and the management of these urban green spaces, including recognition of scales, is crucial to the well-being of the citizens. From a qualitative study of the current management practices in five urban green spaces within the Greater Stockholm Metropolitan Area, Sweden, we found that 1 several spatial, temporal, and functional scales are recognized, but the cross-scale interactions are often neglected, and 2 spatial and temporal meso-scales are seldom given priority. One potential effect of the neglect of ecological cross-scale interactions in these highly fragmented landscapes is a gradual reduction in the capacity of the ecosystems to provide ecosystem services. Two important strategies for overcoming urban scale mismatches are suggested: 1 development of an integrative view of the whole urban social-ecological landscape, and 2 creation of adaptive governance systems to support practical management.

Biocultural Refugia: Combating the Erosion of Diversity in Landscapes of Food Production

Directory of Open Access Journals (Sweden)

Stephan Barthel

2013-12-01

Full Text Available There is urgent need to both reduce the rate of biodiversity loss caused by industrialized agriculture and feed more people. The aim of this paper is to highlight the role of places that harbor traditional ecological knowledge, artifacts, and methods when preserving biodiversity and ecosystem services in landscapes of food production. We use three examples in Europe of biocultural refugia, defined as the physical places that not only shelter farm biodiversity, but also carry knowledge and experiences about practical management of how to produce food while stewarding biodiversity and ecosystem services. Memory carriers include genotypes, landscape features, oral, and artistic traditions and self-organized systems of rules, and as such reflect a diverse portfolio of practices on how to deal with unpredictable change. We find that the rich biodiversity of many regionally distinct cultural landscapes has been maintained through different smallholder practices developed in relation to local environmental fluctuations and carried within biocultural refugia for as long as millennia. Places that transmit traditional ecological knowledge and practices hold important lessons for policy makers since they may provide genetic and cultural reservoirs - refugia - for the wide array of species that have co-evolved with humans in Europe for more than 6000 thousand yrs. Biodiversity restoration projects in domesticated landscapes can employ the biophysical elements and cultural practices embedded in biocultural refugia to create locally adapted small-scale mosaics of habitats that allow species to flourish and adapt to change. We conclude that such insights must be included in discussions of land-sparing vs. land-sharing when producing more food while combating loss of biodiversity. We found the latter strategy rational in domesticated landscapes with a long history of agriculture.

Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China.

Science.gov (United States)

Yang, Qiquan; Huang, Xin; Li, Jiayi

2017-08-24

The urban heat island (UHI) effect exerts a great influence on the Earth's environment and human health and has been the subject of considerable attention. Landscape patterns are among the most important factors relevant to surface UHIs (SUHIs); however, the relationship between SUHIs and landscape patterns is poorly understood over large areas. In this study, the surface UHI intensity (SUHII) is defined as the temperature difference between urban and suburban areas, and the landscape patterns are quantified by the urban-suburban differences in several typical landscape metrics (ΔLMs). Temperature and land-cover classification datasets based on satellite observations were applied to analyze the relationship between SUHII and ΔLMs in 332 cities/city agglomerations distributed in different climatic zones of China. The results indicate that SUHII and its correlations with ΔLMs are profoundly influenced by seasonal, diurnal, and climatic factors. The impacts of different land-cover types on SUHIs are different, and the landscape patterns of the built-up and vegetation (including forest, grassland, and cultivated land) classes have the most significant effects on SUHIs. The results of this study will help us to gain a deeper understanding of the relationship between the SUHI effect and landscape patterns.

[Changes of wetland landscape pattern in Dayang River Estuary based on high-resolution remote sensing image].

Science.gov (United States)

Wu, Tao; Zhao, Dong-zhi; Zhang, Feng-shou; Wei, Bao-quan

2011-07-01

Based on the comprehensive consideration of the high resolution characteristics of remote sensing data and the current situation of land cover and land use in Dayang River Estuary wetland, a classification system with different resolutions of wetland landscape in the Estuary was established. The landscape pattern indices and landscape transition matrix were calculated by using the high resolution remote sensing data, and the dynamic changes of the landscape pattern from 1984 to 2008 were analyzed. In the study period, the wetland landscape components changed drastically. Wetland landscape transferred from natural wetland into artificial wetland, and wetland core regional area decreased. Natural wetland's largest patch area index descended, and the fragmentation degree ascended; while artificial wetland area expanded, its patch number decreased, polymerization degree increased, and the maximum patch area index had an obvious increasing trend. Increasing human activities, embankment construction, and reclamation for aquaculture were the main causes for the decrease of wetland area and the degradation of the ecological functions of Dayang River Estuary. To constitute long-term scientific and reasonable development plan, establish wetland nature reserves, protect riverway, draft strict inspective regimes for aquaculture reclamation, and energetically develop resource-based tourism industry would be the main strategies for the protection of the estuarine wetland.

Operationalizing ecological resilience at a landscape scale: A framework and case study from Silicon Valley

Science.gov (United States)

Beller, E.; Robinson, A.; Grossinger, R.; Grenier, L.; Davenport, A.

2015-12-01

Adaptation to climate change requires redesigning our landscapes and watersheds to maximize ecological resilience at large scales and integrated across urban areas, wildlands, and a diversity of ecosystem types. However, it can be difficult for environmental managers and designers to access, interpret, and apply resilience concepts at meaningful scales and across a range of settings. To address this gap, we produced a Landscape Resilience Framework that synthesizes the latest science on the qualitative mechanisms that drive resilience of ecological functions to climate change and other large-scale stressors. The framework is designed to help translate resilience science into actionable ecosystem conservation and restoration recommendations and adaptation strategies by providing a concise but comprehensive list of considerations that will help integrate resilience concepts into urban design, conservation planning, and natural resource management. The framework is composed of seven principles that represent core attributes which determine the resilience of ecological functions within a landscape. These principles are: setting, process, connectivity, redundancy, diversity/complexity, scale, and people. For each principle we identify several key operationalizable components that help illuminate specific recommendations and actions that are likely to contribute to landscape resilience for locally appropriate species, habitats, and biological processes. We are currently using the framework to develop landscape-scale recommendations for ecological resilience in the heavily urbanized Silicon Valley, California, in collaboration with local agencies, companies, and regional experts. The resilience framework is being applied across the valley, including urban, suburban, and wildland areas and terrestrial and aquatic ecosystems. Ultimately, the framework will underpin the development of strategies that can be implemented to bolster ecological resilience from a site to

Real time automatic scene classification

NARCIS (Netherlands)

Verbrugge, R.; Israël, Menno; Taatgen, N.; van den Broek, Egon; van der Putten, Peter; Schomaker, L.; den Uyl, Marten J.

2004-01-01

This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized

Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

Directory of Open Access Journals (Sweden)

О. О. Dolina

2014-10-01

Full Text Available The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relevant mapping and classification of soils. The classification is adapted to highly-influential industrial conditions of soils formation in the region. The adaptation measures were specific classification levels and units, which provided more detailed differentiation of soils. The authors proposed to separate the soils by the degree of soil formation potential realization for super-divisions. The potential determination allowed predicting the outcome of soil formation and identification of transformation degree of soil cover structures in the region. The results indicated that the main type of soil structures in the industrial region was represented by primitive soils (indicated as a separate type. These soils were determined as dynamic elements in the structure of industrial region soil cover. The article indicated that presence of soil cover structures with the domination of technogenic soils, particularly post-technogenic soils, was the marker of the soil cover in Krivyi Rih Iron-Ore Basin

Laser Raman detection of platelets for early and differential diagnosis of Alzheimer’s disease based on an adaptive Gaussian process classification algorithm

International Nuclear Information System (INIS)

Luo, Yusheng; Du, Z W; Yang, Y J; Chen, P; Wang, X H; Cheng, Y; Peng, J; Shen, A G; Hu, J M; Tian, Q; Shang, X L; Liu, Z C; Yao, X Q; Wang, J Z

2013-01-01

Early and differential diagnosis of Alzheimer’s disease (AD) has puzzled many clinicians. In this work, laser Raman spectroscopy (LRS) was developed to diagnose AD from platelet samples from AD transgenic mice and non-transgenic controls of different ages. An adaptive Gaussian process (GP) classification algorithm was used to re-establish the classification models of early AD, advanced AD and the control group with just two features and the capacity for noise reduction. Compared with the previous multilayer perceptron network method, the GP showed much better classification performance with the same feature set. Besides, spectra of platelets isolated from AD and Parkinson’s disease (PD) mice were also discriminated. Spectral data from 4 month AD (n = 39) and 12 month AD (n = 104) platelets, as well as control data (n = 135), were collected. Prospective application of the algorithm to the data set resulted in a sensitivity of 80%, a specificity of about 100% and a Matthews correlation coefficient of 0.81. Samples from PD (n = 120) platelets were also collected for differentiation from 12 month AD. The results suggest that platelet LRS detection analysis with the GP appears to be an easier and more accurate method than current ones for early and differential diagnosis of AD. (paper)

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

Science.gov (United States)

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…

Adaptation dynamics of the quasispecies model

Indian Academy of Sciences (India)

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 ...

Global hierarchical classification of deepwater and wetland environments from remote sensing products

Science.gov (United States)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

Directory of Open Access Journals (Sweden)

Eduarda Martiniano de Oliveira Silveira

2017-12-01

Full Text Available Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index was generated in an area of Brazilian amazon tropical forest (1,000 km².We selected samples (1 x 1 km from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property and range (φ-the length scale of the spatial structures of objects parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA approaches.

Using graph approach for managing connectivity in integrative landscape modelling

Science.gov (United States)

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.

Cultural adaptation and the Clavien-Dindo surgical complications classification translated to Brazilian Portuguese.

Directory of Open Access Journals (Sweden)

LUIS FERNANDO MOREIRA

Full Text Available ABSTRACT Objective: to generate a translated and validated version of the Clavien-Dindo Classification of Surgical Complications (CDC to Brazilian Portuguese (CDC-BR. Methods: the process of translation and adaptation followed the guideline of Beaton et al., 2000. We divided 76 participating surgeons, in different levels of experience, from the Department Surgery of the Hospital de Clínicas de Porto Alegre, into two groups: Group I applied the original version (CDC, n=36;r Group II used the modified version (CDC-BR, n=40. Each group classified 15 clinical cases of surgical complications. We compared performance between the groups (Mann-Whitney test relating to the level of experience of the surgeon (Kruskal-Wallis test, considering p value <0.05 as significant. Results: the performance of the Group II (CDC-BR was higher, with 85% accuracy, compared with 79% of Group I (CDC, p-value =0.012. The performance of the groups as for surgeons experience displayed p=0.171 for Group I, p=0.528 for Group II, and p=0.135 for overall performance. Conclusion: we produced a translated and validated version of the CDC for Brazilian Portuguese. The instrument will be a useful tool in the production of evidence on surgical outcomes.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

DEFF Research Database (Denmark)

Bothwell, H.; Bisbing, S.; Therkildsen, Nina Overgaard

2013-01-01

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental...... loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi...... variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major...

Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape

Science.gov (United States)

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.

Connecting Brabant's cover sand landscapes through landscape history

Science.gov (United States)

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

Does information on the interdependence of climate adaptation measures stimulate collaboration? A case study analysis

NARCIS (Netherlands)

Vos, Claire C.; Wal, van der Merel M.; Opdam, Paul F.M.; Coninx, Ingrid; Dewulf, Art R.P.J.; Steingröver, Eveliene G.; Stremke, Sven

2018-01-01

A key issue in implementing adaptation strategies at the landscape level is that landowners take measures on their land collectively. We explored the role of information in collective decision-making in a landscape planning process in the Baakse Beek region, the Netherlands. Information was provided

Towards psychologically adaptive brain-computer interfaces

Science.gov (United States)

Myrden, A.; Chau, T.

2016-12-01

Objective. Brain-computer interface (BCI) performance is sensitive to short-term changes in psychological states such as fatigue, frustration, and attention. This paper explores the design of a BCI that can adapt to these short-term changes. Approach. Eleven able-bodied individuals participated in a study during which they used a mental task-based EEG-BCI to play a simple maze navigation game while self-reporting their perceived levels of fatigue, frustration, and attention. In an offline analysis, a regression algorithm was trained to predict changes in these states, yielding Pearson correlation coefficients in excess of 0.45 between the self-reported and predicted states. Two means of fusing the resultant mental state predictions with mental task classification were investigated. First, single-trial mental state predictions were used to predict correct classification by the BCI during each trial. Second, an adaptive BCI was designed that retrained a new classifier for each testing sample using only those training samples for which predicted mental state was similar to that predicted for the current testing sample. Main results. Mental state-based prediction of BCI reliability exceeded chance levels. The adaptive BCI exhibited significant, but practically modest, increases in classification accuracy for five of 11 participants and no significant difference for the remaining six despite a smaller average training set size. Significance. Collectively, these findings indicate that adaptation to psychological state may allow the design of more accurate BCIs.

Application of Source-Sink Landscape Influence Values to Commuter Traffic: A Case Study of Xiamen Island

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Tong Wu

2017-12-01

Full Text Available Landscape patterns are closely related to ecological processes. Different spatial scales and research methods may lead to different results. Therefore, it is crucial to choose suitable research methods when studying different landscape patterns and ecological processes. In the present study, the methods of source-sink landscape theory were applied to the interactions between urban landscape characteristics and commuter traffic behavior around the arterial roads in Xiamen Island. After classification of land use types using remote sensing images from the IKONOS satellite and ArcGIS software (ESRI, Redlands, CA, USA, the landscape patterns of areas surrounding arterial roads (within 1 km were evaluated using source-sink landscape influence (SLI. The results showed that Xiamen Island’s urban expressway had the highest SLI value (0.191, followed by the state highways (0.067, the provincial highways (0.030, and the county roads (0.025. When considering all road types, the correlation between a road’s SLI value and its commuter traffic flow was 0.684. This result was explained by three observations: (1 The contribution of the core area of each landscape pattern to traffic flow was positively correlated with the traffic flow. (2 Areas surrounding the urban expressway and the state highways had lower values for Shannon’s diversity index, indicating that these areas had a lower degree of landscape fragmentation. (3 The landscape patterns surrounding the urban expressway and the state highways were more concentrated and complex than those around other road types. The application of source-sink landscape pattern theory allows for researchers to integrate the relationships between landscape patterns surrounding roads and commuter traffic flow on those roads and to analyze the reasons for these relationships.

Territorial cohesion through cross-border landscape policy? The European case of the Three Countries Park (BE-NL-DE

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Brüll Anja

2017-10-01

Full Text Available Landscapes can be understood as socialecological systems under constant change. In Europe various territorial dynamics pose persistent challenges to maintaining diverse landscapes both as European heritage and in their capacity to provide vital functions and services. Concurrently, under the competence of cohesion policy, the EU is attempting to improve policy making by better policy coordination and respecting regional specifics. This paper explores the question how a policy dedicated to landscape can help to handle territorial change and support territorial cohesion. It presents results and performances of the ESPON applied research study LP3LP: (1 a common landscape policy for the Three Countries Park, across the Dutch, German and Belgium borders, including a spatial landscape vision, a governance proposal of adaptive landscape management, and thematic strategies dealing with green infrastructure, cultural heritage, complementary biomass and quality production; (2 recommendations at the EU level. In discussing the significance of a landscape approach for EU policy,three dimensions of landscape are linked withimportant aspects of territorial cohesion: ‘landscape as asset’ addressing natural-cultural territorial capital as an indigenous base forsmart, sustainable, and inclusivedevelopment;‘landscape as place’ stressing the relevance of landscape for place-based policies; and ‘landscape as common ground’ highlighting its potential for horizontal, vertical, and territorial integration.

Optimization of landscape services under uncoordinated management by multiple landowners.

Directory of Open Access Journals (Sweden)

Miguel Porto

and quantifiable 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.

Chapter 3: Simulating fire hazard across landscapes through time: integrating state-and-transition models with the Fuel Characteristic Classification System

Science.gov (United States)

Jessica E. Halofsky; Stephanie K. Hart; Miles A. Hemstrom; Joshua S. Halofsky; Morris C. Johnson

2014-01-01

Information on the effects of management activities such as fuel reduction treatments and of processes such as vegetation growth and disturbance on fire hazard can help land managers prioritize treatments across a landscape to best meet management goals. State-and-transition models (STMs) allow landscape-scale simulations that incorporate effects of succession,...

A Method for Gauging Landscape Change as a Prelude to Urban Watershed Regeneration: The Case of the Carioca River, Rio de Janeiro

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Vera Regina Tangari

2012-08-01

Full Text Available Natural systems undergo processes, flows, and rhythms that differ from those of urban sociocultural systems. While the former takes place over eras or many generations, the latter may occur within years or even months. Natural systems change includes no principle of intentional progress or enhancement of complexity. In contrast, sociocultural systems change occurs through inherited characteristics, learning, and cultural transmission [1]. Both are dynamic, heterogeneous, and vulnerable to regime shifts, and are inextricably linked. The interrelations among natural and anthropogenic factors affecting sustainability vary spatially and temporally. This paper focuses on landscape changes along the Carioca River valley in Rio de Janeiro, located in the Brazilian Neotropical Southeastern Region, and its implications for local urban sustainability. The study incorporates a transdisciplinary approach that integrates landscape ecology and urban morphology methodologies to gauge landscape change and assess social-ecological systems dynamics. The methodology includes a variety of landscape change assessments; including on-site landscape ecological, landscape morphology, biological and urbanistic surveys, to gauge urban watershed quality. It presents an adapted inventory for assessment of urban tropical rivers, Neotropical Urban Stream Visual Assessment Protocol (NUSVAP, and correlates the level of stream and rainforest integrity to local urban environmental patterns and processes. How can urban regional land managers, planners and communities work together to promote shifts toward more desirable configurations and processes? An understanding of the transient behavior of social-ecological systems and how they respond to change and disturbance is fundamental to building appropriate management strategies and fostering resilience, regenerative capacity, and sustainable development in urban watersheds. The sociocultural patterns, processes and dynamics of Rio�

Modeling Wood Fibre Length in Black Spruce (Picea mariana (Mill. BSP Based on Ecological Land Classification

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Elisha Townshend

2015-09-01

Full Text Available Effective planning to optimize the forest value chain requires accurate and detailed information about the resource; however, estimates of the distribution of fibre properties on the landscape are largely unavailable prior to harvest. Our objective was to fit a model of the tree-level average fibre length related to ecosite classification and other forest inventory variables depicted at the landscape scale. A series of black spruce increment cores were collected at breast height from trees in nine different ecosite groups within the boreal forest of northeastern Ontario, and processed using standard techniques for maceration and fibre length measurement. Regression tree analysis and random forests were used to fit hierarchical classification models and find the most important predictor variables for the response variable area-weighted mean stem-level fibre length. Ecosite group was the best predictor in the regression tree. Longer mean fibre-length was associated with more productive ecosites that supported faster growth. The explanatory power of the model of fitted data was good; however, random forests simulations indicated poor generalizability. These results suggest the potential to develop localized models linking wood fibre length in black spruce to landscape-level attributes, and improve the sustainability of forest management by identifying ideal locations to harvest wood that has desirable fibre characteristics.

From Synergy to Complexity: The Trend Toward Integrated Value Chain and Landscape Governance.

Science.gov (United States)

Ros-Tonen, Mirjam A F; Reed, James; Sunderland, Terry

2018-05-30

This Editorial introduces a special issue that illustrates a trend toward integrated landscape approaches. Whereas two papers echo older "win-win" strategies based on the trade of non-timber forest products, ten papers reflect a shift from a product to landscape perspective. However, they differ from integrated landscape approaches in that they emanate from sectorial approaches driven primarily by aims such as forest restoration, sustainable commodity sourcing, natural resource management, or carbon emission reduction. The potential of such initiatives for integrated landscape governance and achieving landscape-level outcomes has hitherto been largely unaddressed in the literature on integrated landscape approaches. This special issue addresses this gap, with a focus on actor constellations and institutional arrangements emerging in the transition from sectorial to integrated approaches. This editorial discusses the trends arising from the papers, including the need for a commonly shared concern and sense of urgency; inclusive stakeholder engagement; accommodating and coordinating polycentric governance in landscapes beset with institutional fragmentation and jurisdictional mismatches; alignment with locally embedded initiatives and governance structures; and a framework to assess and monitor the performance of integrated multi-stakeholder approaches. We conclude that, despite a growing tendency toward integrated approaches at the landscape level, inherent landscape complexity renders persistent and significant challenges such as balancing multiple objectives, equitable inclusion of all relevant stakeholders, dealing with power and gender asymmetries, adaptive management based on participatory outcome monitoring, and moving beyond existing administrative, jurisdictional, and sectorial silos. Multi-stakeholder platforms and bridging organizations and individuals are seen as key in overcoming such challenges.

Identification and Typology of Czech Postindustrial Landscapes on National Level Using GIS and Publicly Accessed Geodatabases

Czech Academy of Sciences Publication Activity Database

Kolejka, Jaromír; Klimánek, M.

2015-01-01

Roč. 34, č. 2 (2015), s. 121-136 ISSN 1335-342X R&D Projects: GA AV ČR IAA300860903 Institutional support: RVO:68145535 Keywords : industrial heritage * landscapes * mapping * classification Subject RIV: DE - Earth Magnetism, Geodesy, Geography https://www.degruyter.com/downloadpdf/j/eko.2015.34.issue-2/eko-2015-0013/eko-2015-0013.pdf

Conceptions of Landscape-Ecological Relevance Emerged in the Czech Botany during the Second Half of Twentieth Century

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Kovář Pavel

2015-12-01

Full Text Available This paper summarizes those substantial theoretical concepts or methods for applications within interdisciplinary or practical uses published by Czech autors (geobotanists = ecological botanists, plant ecologists and ecophysiologists during the second half of the 20th century, that were internationally cited. All selected thematical clusters are of landscape-ecological relevance through various contexts. Examples include the concepts of (potential reconstructed vegetation in maps (R. Neuhäusl, Z. Neuhäuslová, linear vegetation features (corridors in landscape and deductive classification of vegetation (K. Kopecký, analysis of soil seed bank (Z. Kropáč, dependency of macrophyte plant stands on ecodynamics (S. Hejný, dynamic periodicity in segetal vegetation (Z. Kropáč, E. Hadač, S. Hejný, anemo-orographic system explaining species richness in mountain regions (J. Jeník, productivity in grassland ecosystems (M. Rychnovská, J. Květ, elementary landscape units based on homogenity and potential vegetation (E. Hadač, landscape dispensation phenomena (V. Ložek, afforestation of coastal sandy dunes – the Netherlands, and polluted areas - the Czech Republic (J. Fanta, invasive plants and invasions into landscapes (M. Rejmánek.

Classification of supersymmetric backgrounds of string theory

NARCIS (Netherlands)

Gran, Ulf; Gutowski, Jan; Papadopoulos, George; Roest, Diederik

2007-01-01

We review the recent progress made towards the classification of supersymmetric solutions in ten and eleven dimensions with emphasis on those of IIB supergravity. In particular, the spinorial geometry method is outlined and adapted to nearly maximally supersymmetric backgrounds.We then demonstrate

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

Science.gov (United States)

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2016-01-01

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis, and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua. Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive

Planetary Landscape Geography

Science.gov (United States)

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

A new approach to the identification of Landscape Quality Objectives (LQOs) as a set of indicators.

Science.gov (United States)

Sowińska-Świerkosz, Barbara Natalia; Chmielewski, Tadeusz J

2016-12-15

The objective of the paper is threefold: (1) to introduce Landscape Quality Objectives (LQOs) as a set of indicators; (2) to present a method of linking social and expert opinion in the process of the formulation of landscape indicators; and (3) to present a methodological framework for the identification of LQOs. The implementation of these goals adopted a six-stage procedure based on the use of landscape units: (1) GIS analysis; (2) classification; (3) social survey; (4) expert value judgement; (5) quality assessment; and (6) guidelines formulation. The essence of the research was the presentation of features that determine landscape quality according to public opinion as a set of indicators. The results showed that 80 such indicators were identified, of both a qualitative (49) and a quantitative character (31). Among the analysed units, 60% (18 objects) featured socially expected (and confirmed by experts) levels of landscape quality, and 20% (6 objects) required overall quality improvement in terms of both public and expert opinion. The adopted procedure provides a new tool for integrating social responsibility into environmental management. The advantage of the presented method is the possibility of its application in the territories of various European countries. It is flexible enough to be based on cartographic studies, landscape research methods, and environmental quality standards existing in a given country. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimizing Input/Output Using Adaptive File System Policies

Science.gov (United States)

Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

1996-01-01

Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

Changing Landscapes, Changing Landscape's Story

Czech Academy of Sciences Publication Activity Database

Lapka, Miloslav; Cudlínová, Eva

2003-01-01

Roč. 28, č. 3 (2003), s. 323-328 ISSN 0142-6397. [Symposium on Sustainable Landscapes in an Enlarged Europe. Nové Hrady, 12.09.2001-14.09.2001] R&D Projects: GA MŠk ME 530 Grant - others:GA-(XE) QLK5-CT-2000-01211-SPRITE Institutional research plan: CEZ:AV0Z5039906 Keywords : Landscape stability * narrative approach * socio-economic typology Subject RIV: DO - Wilderness Conservation

Monitoring adaptive genetic responses to environmental change

DEFF Research Database (Denmark)

Hansen, M.M.; Olivieri, I.; Waller, D.M.

2012-01-01

Widespread environmental changes including climate change, selective harvesting and landscape alterations now greatly affect selection regimes for most organisms. How animals and plants can adapt to these altered environments via contemporary evolution is thus of strong interest. We discuss how...... for selection and establishing clear links between genetic and environmental change. We then review a few exemplary studies that explore adaptive responses to climate change in Drosophila, selective responses to hunting and fishing, and contemporary evolution in Daphnia using resurrected resting eggs. We...

Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

Science.gov (United States)

McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

1999-01-01

This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

Energy Technology Data Exchange (ETDEWEB)

Diane De Steven,Ph.D.; Maureen Tone,PhD.

1997-10-01

This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicate floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Combs, Stephanie E., E-mail: Stephanie.Combs@med.uni-heidelberg.de [Department of Radiation Oncology, University Hospital of Heidelberg, Heidelberg (Germany); Schulz-Ertner, Daniela [Radiologisches Institut, Markuskrankenhaus Frankfurt, Frankfurt am Main (Germany); Debus, Juergen [Department of Radiation Oncology, University Hospital of Heidelberg, Heidelberg (Germany); Deimling, Andreas von; Hartmann, Christian [Department of Neuropathology, Institute for Pathology, University Hospital of Heidelberg, Heidelberg (Germany); Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Heidelberg (Germany)

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

Characterizing European cultural landscapes

DEFF Research Database (Denmark)

Tieskens, Koen F.; Schulp, Catharina J E; Levers, Christian

2017-01-01

intensification and land abandonment. To prevent the loss of cultural landscapes, knowledge on the location of different types of cultural landscapes is needed. In this paper, we present a characterization of European cultural landscapes based on the prevalence of three key dimensions of cultural landscapes......Almost all rural areas in Europe have been shaped or altered by humans and can be considered cultural landscapes, many of which now are considered to entail valuable cultural heritage. Current dynamics in land management have put cultural landscapes under a huge pressure of agricultural...... the three dimensions into a continuous “cultural landscape index” that allows for a characterization of Europe's rural landscapes. The characterization identifies hotspots of cultural landscapes, where all three dimensions are present, such as in the Mediterranean. On the other hand, Eastern and Northern...

Multifunctional landscape practice and accessibility in manorial landscapes

DEFF Research Database (Denmark)

Brandt, Jesper; Svenningsen, Stig Roar; Christensen, Andreas Aagaard

. However classical manorial estates seems to represent an opposite trend. Allthough working at the same market conditions as other large specialized holdings developed through the process of structural rationalization, they have often maintained and elaborated a land use strategy based on a multifunctional...... use of the potential ecosystem services present within their domain. The targeted combination of agriculture, forestry, hunting rents, rental housing, and a variety of recreational activities influences makes a certain public accessibility to an integrated part of this strategy, diverging from...... the multifunctional landscape strategy supporting a certain public access. A study of this thesis is presented based on an analysis of multifunctionality, landscape development and accessibility in Danish Manorial landscapes and eventual linkages between their multifunctional landscape strategy, their history...

Beyond Landscape MacArchitecture: new languages, new landscapes

Directory of Open Access Journals (Sweden)

Simon Rackham

1996-03-01

Full Text Available The sine qua non of landscape architecture is respect for the genius loci, but even in the landscape, as in architecture and society more generally, a process of cultural homogenisation has been taking place. Against this process, a resurgence of interest in minority languages in Europe can be seen as an assertion of pride, and a desire to preserve difference. In Scotland, landscape architects are attempting to reinterpret Scottish and northern European urban design influences and materials: in effect to develop a new regional dialect for the new landscapes. Rooted in sound design principles and materials which respond to and reflect the climate, way of life and traditions of the place, design languages can communicate effectively about cultural values and differences.

PESP Landscaping Initiative

Science.gov (United States)

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.

Risk-adaptive optimization: Selective boosting of high-risk tumor subvolumes

International Nuclear Information System (INIS)

Kim, Yusung; Tome, Wolfgang A.

2006-01-01

Background and Purpose: A tumor subvolume-based, risk-adaptive optimization strategy is presented. Methods and Materials: Risk-adaptive optimization employs a biologic objective function instead of an objective function based on physical dose constraints. Using this biologic objective function, tumor control probability (TCP) is maximized for different tumor risk regions while at the same time minimizing normal tissue complication probability (NTCP) for organs at risk. The feasibility of risk-adaptive optimization was investigated for a variety of tumor subvolume geometries, risk-levels, and slopes of the TCP curve. Furthermore, the impact of a correlation parameter, δ, between TCP and NTCP on risk-adaptive optimization was investigated. Results: Employing risk-adaptive optimization, it is possible in a prostate cancer model to increase the equivalent uniform dose (EUD) by up to 35.4 Gy in tumor subvolumes having the highest risk classification without increasing predicted normal tissue complications in organs at risk. For all tumor subvolume geometries investigated, we found that the EUD to high-risk tumor subvolumes could be increased significantly without increasing normal tissue complications above those expected from a treatment plan aiming for uniform dose coverage of the planning target volume. We furthermore found that the tumor subvolume with the highest risk classification had the largest influence on the design of the risk-adaptive dose distribution. The parameter δ had little effect on risk-adaptive optimization. However, the clinical parameters D 5 and γ 5 that represent the risk classification of tumor subvolumes had the largest impact on risk-adaptive optimization. Conclusions: On the whole, risk-adaptive optimization yields heterogeneous dose distributions that match the risk level distribution of different subvolumes within the tumor volume

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.

Science.gov (United States)

Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias

2017-11-03

Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya

Directory of Open Access Journals (Sweden)

Kyalo Richard

2017-11-01

Full Text Available Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step. An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer’s accuracy and UA: user’s accuracy for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10–20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

Science.gov (United States)

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...

Changing Histopathological Diagnostics by Genome-Based Tumor Classification

Directory of Open Access Journals (Sweden)

Michael Kloth

2014-05-01

Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

Coupling movement and landscape ecology for animal conservation in production landscapes.

Science.gov (United States)

Doherty, Tim S; Driscoll, Don A

2018-01-10

Habitat conversion in production landscapes is among the greatest threats to biodiversity, not least because it can disrupt animal movement. Using the movement ecology framework, we review animal movement in production landscapes, including areas managed for agriculture and forestry. We consider internal and external drivers of altered animal movement and how this affects navigation and motion capacities and population dynamics. Conventional management approaches in fragmented landscapes focus on promoting connectivity using structural changes in the landscape. However, a movement ecology perspective emphasizes that manipulating the internal motivations or navigation capacity of animals represents untapped opportunities to improve movement and the effectiveness of structural connectivity investments. Integrating movement and landscape ecology opens new opportunities for conservation management in production landscapes. © 2018 The Authors.

Classification schemes for knowledge translation interventions: a practical resource for researchers.

Science.gov (United States)

Slaughter, Susan E; Zimmermann, Gabrielle L; Nuspl, Megan; Hanson, Heather M; Albrecht, Lauren; Esmail, Rosmin; Sauro, Khara; Newton, Amanda S; Donald, Maoliosa; Dyson, Michele P; Thomson, Denise; Hartling, Lisa

2017-12-06

As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability

Adaptive nonparametric Bayesian inference using location-scale mixture priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2010-01-01

We study location-scale mixture priors for nonparametric statistical problems, including multivariate regression, density estimation and classification. We show that a rate-adaptive procedure can be obtained if the prior is properly constructed. In particular, we show that adaptation is achieved if

Impact of CO2 emissions on the geoecological state of landscapes of the British Isles: carbon footprint versus the assimilation potential

Science.gov (United States)

Romanova, Emma; Bulokhov, Anton; Arshinova, Marina

2017-04-01

The geoecological state of landscapes is determined by the type and intensity of anthropogenic impacts, the ability of geosystems to sustain them and the number of population living within a particular landscape unit. The main sources of CO2 emissions are thermal power plants, industrial facilities, transport and waste utilization. In Great Britain 163 enterprises produce 254.7 MMT CO2Eq. and 20 enterprises in Ireland - 17.8 MMT CO2Eq. Total transport emissions are 122 MMT CO2Eq. Utilization of solid wastes collected on the British Isles produces about 4.2 MMT CO2Eq. The spatial pattern of CO2 sources within the landscapes is particularly mosaic. Among the indicators which characterize the capacity of landscapes to neutralize wastes the assimilation potential (AP) is particularly important. The neutralization is based on the process of sequestration of gaseous substances, i.e. their accumulation in leaves, branches and stocks during respiration and growth of trees and in water bodies by aquatic organisms. Thus the AP is calculated basing on the area of forests and wetlands which perform the regulating services in landscapes. Total absorbing capacity of forests of the British Isles is 6.805 MMT CO2Eq. Inland waters cover 0.01% of the territory and their assimilating role is minor. The evaluation procedure includes several analytical steps: 1) inventory of the volumes of CO2 emissions by all anthropogenic sources within the borders of natural geosystems; 2) calculation of the area of CO2 assimilation in landscapes and the maximum possible volumes of CO2 sequestration; 3) comparison of the volumes of emissions and the assimilation potential of each landscape, classification of landscapes into debtors (with the deficit of AP) and creditors (with surplus AP); 4) calculation of population in each landscape; 5) risk assessment for the inhabitants living within landscapes-debtors; 6) classification and mapping of landscapes according to their geoecological state. The

Examining the Role of Cultural Landscape in Regional Development: Defining Criteria and Looking at Ephesus

Directory of Open Access Journals (Sweden)

Gökçe Şimşek

2017-06-01

Full Text Available The link between regional development and cultural heritage has been at the center of theoretical discussions and practices in the field of preservation. Especially, varieties of practices and regional plans have been developed in different parts of the World such as Europe, Russia and South Africa in order to ensure regional development through cultural heritage. In this paper, it is accepted that a cultural landscape, as a sub-region of a particular region, is a relevant and meaningful unit that can contribute to the qualities of the region in terms of socio-cultural and economic aspects. In this context, the main goal of this paper is to develop a set of criteria that will act as a tool for identifying to which aspects of a cultural landscape has the potential to contribute regional development and to evaluate possible contributions of Ephesus and its cultural landscape to regional development. These criteria can be classified according to a framework implying a three-fold classification; improvements in the physical quality of the cultural landscape, economic dimension and socio-cultural dimension. As a result, this case indicates that cultural landscape has great potential to contribute to the social and economic development of a region. There is a great need to support community through tools such as awareness raising programmes, regional heritage planning, regional heritage institutions acting as regional agencies.

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

Science.gov (United States)

Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

Hierarchically structured identification and classification method for vibrational monitoring of reactor components

International Nuclear Information System (INIS)

Saedtler, E.

1981-01-01

The dissertation discusses: 1. Approximative filter algorithms for identification of systems and hierarchical structures. 2. Adaptive statistical pattern recognition and classification. 3. Parameter selection, extraction, and modelling for an automatic control system. 4. Design of a decision tree and an adaptive diagnostic system. (orig./RW) [de

Understanding the whole city as landscape. A multivariate approach to urban landscape morphology

Directory of Open Access Journals (Sweden)

Richard Stiles

2014-05-01

Full Text Available The European Landscape Convention implies a requirement for signatory states to identify their urban landscapes which goes beyond the traditional focus on individual parks and green spaces and the links between them. Landscape ecological approaches can provide a useful model for identifying urban landscape types across a whole territory, but the variables relevant for urban landscapes are very different to those usually addressing rural areas. This paper presents an approach to classifying the urban landscape of Vienna that was developed in a research project funded by the Austrian Ministry for Transport, Innovation and Technology: ‘Urban Fabric and Microclimate Response’. Nine landscape types and a number of sub-types were defined, using a multivariate statistical approach which takes account of both morphological and urban climate related variables. Although the variables were selected to objectively reflect the factors that could best represent the urban climatic characteristics of the urban landscape, the results also provided a widely plausible representation of the structure of the city’s landscapes. Selected examples of the landscape types that were defined in this way were used both to simulate current microclimatic conditions and also to model the effects of possible climatic amelioration measures. Finally the paper looks forward to developing a more general-purpose urban landscape typology that allows investigating a much broader complex of urban landscape functions.

Urban landscape infrastructures: Designing operative landscape structures for the built environment

OpenAIRE

Nijhuis, S.; Jauslin, D.T.

2015-01-01

This paper explores infrastructure as a type of landscape and landscape as a type of infrastructure. The hybridisation of the two concepts, landscape and infrastructure, seeks to redefine infrastructure beyond its strictly utilitarian definition, while allowing design disciplines to gain operative force in territorial transformation processes. This paper aims to put forward urban landscape infrastructures as a design concept, considering them as armatures for urban development and for facilit...

Contemporary danish landscape research

DEFF Research Database (Denmark)

Vejre, H.; Brandt, J.

2004-01-01

Danish landscape research blossomed during the 1990’ies thanks to several transdisciplinary research programmes involving several institutions. The main themes of the programmes encompassed Landscape change, landscape and biological diversity, nature and landscape management, use and monitoring...

Detecting consistent patterns of directional adaptation using differential selection codon models.

Science.gov (United States)

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

[Knowledge produced from the outcomes of the "Nursing Outcomes Classification--NOC": integrative review].

Science.gov (United States)

da Silva, Natália Chantal Magalhães; de Souza Oliveira, Ana Railka; de Carvalho, Emília Campos

2015-12-01

To identify the knowledge produced from the outcomes of the Nursing Outcomes Classification (NOC). A literature review using the integrative databases: Latin American and Caribbean Health Sciences (LILACS), US National Library of Medicine (PubMed), Cumulative Index to Nursing & Allied Health Literature (CINAHL) and Scopus Info Site (SCOPUS), during the months of August and September 2014. The review consisted of 21 articles that addressed different issues: Translation and Cultural adaptation (4.77%); Applicability in clinical practice (33.33%); and, Validation (63.90%). Analysis of these articles showed that the knowledge produced from the Nursing Outcomes Classification includes translation and cultural adaptation, evaluation of applicability and validation of its items. Considering the continuous evolution of this classification, periodic reviews should be carried out to identify the knowledge, use and effects of the NOC.

Adaptive distributed outlier detection for WSNs.

Science.gov (United States)

De Paola, Alessandra; Gaglio, Salvatore; Lo Re, Giuseppe; Milazzo, Fabrizio; Ortolani, Marco

2015-05-01

The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication complexity, and also considering externally imposed constraints on such conflicting goals. The performed experimental evaluation showed that our approach is able to improve the considered metrics for latency and energy consumption, with limited impact on classification accuracy.

Top-k Based Adaptive Enumeration in Constraint Programming

Directory of Open Access Journals (Sweden)

Ricardo Soto

2015-01-01

order for variables and values is employed along the search. In this paper, we present a new and more lightweight approach for performing adaptive enumeration. We incorporate a powerful classification technique named Top-k in order to adaptively select strategies along the resolution. We report results on a set of well-known benchmarks where the proposed approach noticeably competes with classical and modern adaptive enumeration methods for constraint satisfaction.

Towards a regional beef carcass classification system for Southern ...

African Journals Online (AJOL)

Mapiye, C, Dr

2017-05-15

May 15, 2017 ... beef carcass grading and classification systems used in the region ..... between cattle breeds (genetic), pre-slaughter stress and growth- ..... Nguni cattle for example, owing to their adaptability (i.e. drought and heat tolerant,.

Responding to Landscape Change: Stakeholder Participation and Social Capital in Five European Landscapes

Directory of Open Access Journals (Sweden)

Thanasis Kizos

2018-01-01

Full Text Available The concept of landscape has been increasingly used, in the last decades, in policy and land use planning, both in regard to so-called “special” and to “ordinary” or “everyday” landscapes. This has raised the importance of local and public participation in all issues that refer to landscapes and the definition of the groups that “have a stake” in the landscape. In this paper, we provide insights into how stakeholders perceive the dynamics of local processes of landscape change (and continuity and which processes of landscape change they perceive as important, in positive and negative ways, from five communities within the European Union. These landscapes involve different landscape issues “at stake”, different national and local planning and decision-making traditions and practices, and varying degrees of engagement. The understanding of these complexities and the unraveling of the insights is done through the concept of social capital and its different forms. We report on three series of workshops that have been organized to discuss landscape issues and approaches or ideas for landscape management. We witnessed interactions between the different stakeholders and gained insights into how social capital affects landscape change. We found that despite differences, similarities emerged concerning the interplay between “expert” and “local” knowledge and between “insideness” and “outsideness”. Social capital plays an important part, as it provides the template for personal and collective evaluation of landscape changes, who should manage these changes and how they should be managed. These findings are important to develop in-depth insights on dynamics and values of cultural landscapes and visions for re-coupling social and ecological components in cultural landscapes and translate them into policy and management options.

SUSTAINABLE URBAN LANDSCAPE: AN APPROACH FOR ASSESSING AND APPROPRIATING INDICATORS

Directory of Open Access Journals (Sweden)

Ahmed Mohamed Amin

2012-07-01

Full Text Available The impact of development on its context is considered a key issue that governs the discussion and understanding of sustainability. For the reason, that ethics of sustainability are based on developing with no or less negative impacts on the contextual environment despite its urban scale whether limited or extended. This describes types of development that increase the good impacts on the tangible and intangible aspects of the built environment. Thus, achieving sustainability is no more a choice but it is a must especially, in an environment suffering from a lot of threats and stresses that affect all aspects of life; socially, economically, environmentally and also affect the beauty and aesthetics of urban fabrics. Assessing sustainability, the applied indicators and ways of assessment are allimportant concerns for urban sustainability discourses. Especially in such sensitive interacting domains as landscape, that links nature with the built environment. Approaching these concerns has a great deal when enhancing our environment aiming at better urban life containers. This paper aims at investigating the issue of sustainable urban landscape assessment through discussing the hue of indicators, their ways of classification, the criteria of selection and stating the variety of methods in which they can be assessed. Finally, it appropriates an approach for stating and assessing urban landscape sustainability indicators, which evaluates their both qualitative and quantitative value upon performance scale.

Urban landscape infrastructures : Designing operative landscape structures for the built environment

NARCIS (Netherlands)

Nijhuis, S.; Jauslin, D.T.

2015-01-01

This paper explores infrastructure as a type of landscape and landscape as a type of infrastructure. The hybridisation of the two concepts, landscape and infrastructure, seeks to redefine infrastructure beyond its strictly utilitarian definition, while allowing design disciplines to gain operative

Geotechnology and landscape ecology applied to the selection of potential forest fragments for seed harvesting.

Science.gov (United States)

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Creating adaptive farm typologies using Naive Bayesian classification

NARCIS (Netherlands)

Paas, Wim; Groot, Jeroen C.J.

2017-01-01

The applicability of statistical typologies that capture farming systems diversity in innovation and development projects would increase if their adaptability would be enhanced, so that newly encountered farms can be classified and used to update the typology. In this paper we propose Naïve

Knowledge production and learning for sustainable landscapes: seven steps using social-ecological systems as laboratories.

Science.gov (United States)

Angelstam, Per; Elbakidze, Marine; Axelsson, Robert; Dixelius, Malcolm; Törnblom, Johan

2013-03-01

There are multiple challenges regarding use and governance of landscapes' goods, functions and intangible values for ecosystem health and human well-being. One group of challenges is to measure and assess principal sustainability dimensions through performance targets, so stakeholders have transparent information about states and trends. Another group is to develop adaptive governance at multiple levels, and management of larger geographical areas across scales. Addressing these challenges, we present a framework for transdisciplinary research using multiple landscapes as place-based case studies that integrates multiple research disciplines and non-academic actors: (1) identify a suite of landscapes, and for each (2) review landscape history, (3) map stakeholders, use and non-use values, products and land use, (4) analyze institutions, policies and the system of governance, (5) measure ecological, economic, social and cultural sustainability, (6) assess sustainability dimensions and governance, and finally (7) make comparisons and synthesize. Collaboration, communication and dissemination are additional core features. We discuss barriers bridges and bridges for applying this approach.

[Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

Science.gov (United States)

Liang, Jia Xin; Li, Xin Ju

2018-02-01

With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

Untangling natural seascape variation from marine reserve effects using a landscape approach.

Directory of Open Access Journals (Sweden)

Brittany E Huntington

Full Text Available Distinguishing management effects from the inherent variability in a system is a key consideration in assessing reserve efficacy. Here, we demonstrate how seascape heterogeneity, defined as the spatial configuration and composition of coral reef habitats, can mask our ability to discern reserve effects. We then test the application of a landscape approach, utilizing advances in benthic habitat mapping and GIS techniques, to quantify this heterogeneity and alleviate the confounding influence during reserve assessment. Seascape metrics were quantified at multiple spatial scales using a combination of spatial image analysis and in situ surveys at 87 patch reef sites in Glover's Reef Lagoon, Belize, within and outside a marine reserve enforced since 1998. Patch reef sites were then clustered into classes sharing similar seascape attributes using metrics that correlated significantly to observed variations in both fish and coral communities. When the efficacy of the marine reserve was assessed without including landscape attributes, no reserve effects were detected in the diversity and abundance of fish and coral communities, despite 10 years of management protection. However, grouping sites based on landscape attributes revealed significant reserve effects between site classes. Fish had higher total biomass (1.5x and commercially important biomass (1.75x inside the reserve and coral cover was 1.8 times greater inside the reserve, though direction and degree of response varied by seascape class. Our findings show that the application of a landscape classification approach vastly improves our ability to evaluate the efficacy of marine reserves by controlling for confounding effects of seascape heterogeneity and suggests that landscape heterogeneity should be considered in future reserve design.

Africa and climate change: Adapt, survive, thrive? | IDRC ...

International Development Research Centre (IDRC) Digital Library (Canada)

2011-01-27

Jan 27, 2011 ... Faced with a changing climate, projects to help Africans adapt are springing up across the continent. Across the continent of Africa, the landscape is changing. ... Africa' (CCAA) — jointly funded by the Canadian International Development Research Centre .... Computers for Schools Kenya at top of the class.

Aspects of Cultural Landscape Application on Classical Stage Art. Ballet Performance in the Open Space as a Significant Element of the Cultural Landscape

Directory of Open Access Journals (Sweden)

Jelena Lebedeva

2016-04-01

Full Text Available The article examines the applications aspects of cultural landscape for the preparation of the classical performing arts staging. Research findings highlighted that the cultural landscape (parks, estates, castles, bastions, etc. objects occupies an increasingly important role in public recreation and classical art development programs. At the same time it is noted that event’s aesthetic and emotional quality suffers due to the fact that no specific attention was given for the preparation of the event space. More methodological materials are necessary for preparation of this type of design spaces. In Lithuania classical performing arts events in cultural landscape open spaces are based on XVI–XVII century tradition and has good prospects for modern development. A review of some of the classical art events installations, based on the importance of quality of open spaces influence on the emotional impact, that should be an integral part of the cultural event. The author summarizes his experience of ballet events in open spaces in the cultural landscape – Klaipėda, Trakai. Presented is Tchaikovsky's ballet “Swan Lake” construction in Klaipėda John Hill project that includes infrastructure and environmental design concept: audience space, stage design, stage design performance solutions. Analogous key decisions are later adapted to the ballet performance in the natural environment of the lake Trakai. Experience of this project dictated the necessity of deeper understanding and methodological basis for the classical performing arts analysis and design.

Fuel dynamics by using Landscape Ecology Indices in the Alto Mijares, Spain

Science.gov (United States)

Iqbal, J.; Garcia, C. V.

2009-04-01

Land abandonment in Mediterranean regions has brought about a number of management problems, being an increased wildfire activity prevalent among them. Agricultural neglect in highlands resulted in reduced anthropogenic disturbances and greater landscape homogeneity in areas such as the Alto Mijares in Spain. It is widely accepted that processes like forest fires, influence structure of the landscape and vice versa. Fire-prone Mediterranean flora is well adapted to this disturbance, exhibiting excellent succession capabilities; but higher fuel loads and homogeneous conditions may ally to promote vegetation recession when the fire regime is altered by land abandonment. Both succession and recession make changes to the landscape structure and configuration. However, these changes are difficult to quantify and characterize. If landscape restoration of these forests is a management objective, then developing a quantitative knowledge base for landscape fuel dynamics is a prerequisite. Four classified LandsatTM satellite images were compared to quantify changes in landscape structure between 1984 and 1998. An attempt is made to define landscape level dynamics for fuel development after reduced disturbance and fuel accumulation that leads to catastrophic fires by using landscape ecology indices. By doing so, indices that best describe the fuel dynamics are pointed. The results indicate that low-level disturbance increases heterogeneity, thus lowers fire hazard. No disturbance or severe disturbance increases homogeneity because of vegetation succession and may lead to devastating fires. These fires could be avoided by human induced disturbance like controlled burning, harvesting, mechanical works for fuel reduction and other silviculture measures; thus bringing in more heterogeneity in the region. The Alto Mijares landscape appears to be in an unstable equilibrium where succession and recession are at tug of war. The effects are evident in the general absence of the climax

Evidence and opportunities for integrating landscape ecology into natural resource planning across multiple-use landscapes

Science.gov (United States)

Trammel, E. Jamie; Carter, Sarah; Haby, Travis S.; Taylor, Jason J.

2018-01-01

Enhancing natural resource management has been a focus of landscape ecology since its inception, but numerous authors argue that landscape ecology has not yet been effective in achieving the underlying goal of planning and designing sustainable landscapes. We developed nine questions reflecting the application of fundamental research topics in landscape ecology to the landscape planning process and reviewed two recent landscape-scale plans in western North America for evidence of these concepts in plan decisions. Both plans considered multiple resources, uses, and values, including energy development, recreation, conservation, and protection of cultural and historic resources. We found that land use change and multiscale perspectives of resource uses and values were very often apparent in planning decisions. Pattern-process relationships, connectivity and fragmentation, ecosystem services, landscape history, and climate change were reflected less frequently. Landscape sustainability was considered only once in the 295 decisions reviewed, and outputs of landscape models were not referenced. We suggest six actionable opportunities for further integrating landscape ecology concepts into landscape planning efforts: 1) use landscape sustainability as an overarching goal, 2) adopt a broad ecosystem services framework, 3) explore the role of landscape history more comprehensively, 4) regularly consider and accommodate potential effects of climate change, 5) use landscape models to support plan decisions, and 6) promote a greater presence of landscape ecologists within agencies that manage large land bases and encourage active involvement in agency planning efforts. Together these actions may improve the defensibility, durability, and sustainability of landscape plan decisions.

QUEST : Eliminating online supervised learning for efficient classification algorithms

NARCIS (Netherlands)

Zwartjes, Ardjan; Havinga, Paul J.M.; Smit, Gerard J.M.; Hurink, Johann L.

2016-01-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting

The String Landscape: A Personal Perspective

Science.gov (United States)

Dienes, Keith R.

2015-02-01

In keeping with the "Perspectives" theme of this volume, this Chapter provides a personal perspective on the string landscape. Along the way, the perspectives of many other physicists are discussed as well. No attempt is made to provide a thorough and balanced review of the field, and indeed there is a slight emphasis on my own contributions to this field, as these contributions have been critical to forming my perspective. This Chapter is adapted from a Colloquium which I have delivered at a number of institutions worldwide, and I have attempted to retain the informal and non-technical spirit and style of this Colloquium presentation as much as possible.

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

Science.gov (United States)

: 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...

Landscape stability and water management around the ancient city Jerash, Jordan

DEFF Research Database (Denmark)

Holdridge, Genevieve; Thomsen, K; Kristiansen, Søren Munch

2017-01-01

approach that incorporates archaeological, paleoclimatic, and geomorphological information, our objective is to discern natural and anthropogenic influences on land and water management. In order to explore human adaptation and impact, we have examined both on- and off-site urban stratigraphy...... provide much needed information on the beneficial and adverse impacts this adaptation had on the surrounding landscape and local dryland fluvial system.......Reduced vulnerability to environmental fluctuations by increasing food and water security increases the resilience of a human society. In the Middle East, there is much archaeological evidence of steady developments and abrupt disasters in cities that have occurred over the millennia, while...

Knowledge produced from the outcomes of the "Nursing Outcomes Classification - NOC": integrative review

Directory of Open Access Journals (Sweden)

Natália Chantal Magalhães da Silva

Full Text Available Objective: To identify the knowledge produced from the outcomes of the Nursing Outcomes Classification (NOC. Method: A literature review using the integrative databases: Latin American and Caribbean Health Sciences (LILACS, US National Library of Medicine (PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL and Scopus Info Site (SCOPUS, during the months of August and September 2014. Results: The review consisted of 21 articles that addressed different issues: Translation and Cultural adaptation (4.77%; Applicability in clinical practice (33.33%; and, Validation (63.90%. Analysis of these articles showed that the knowledge produced from the Nursing Outcomes Classification includes translation and cultural adaptation, evaluation of applicability and validation of its items. Conclusion: Considering the continuous evolution of this classification, periodic reviews should be carried out to identify the knowledge, use and effects of the NOC.

A Novel Texture Classification Procedure by using Association Rules

Directory of Open Access Journals (Sweden)

L. Jaba Sheela

2008-11-01

Full Text Available Texture can be defined as a local statistical pattern of texture primitives in observer’s domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules have been used in various applications during the past decades. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules. The overall success rate is about 98%.

GIS-based landscape design research: Stourhead landscape garden as a case study

Directory of Open Access Journals (Sweden)

Steffen Nijhuis

2017-11-01

Full Text Available Landscape design research is important for cultivating spatial intelligence in landscape architecture. This study explores GIS (geographic information systems as a tool for landscape design research - investigating landscape designs to understand them as architectonic compositions (architectonic plan analysis. The concept ‘composition’ refers to a conceivable arrangement, an architectural expression of a mental construct that is legible and open to interpretation. Landscape architectonic compositions and their representations embody a great wealth of design knowledge as objects of our material culture and reflect the possible treatment of the ground, space, image and program as a characteristic coherence. By exploring landscape architectonic compositions with GIS, design researchers can acquire design knowledge that can be used in the creation and refinement of a design.  The research aims to identify and illustrate the potential role of GIS as a tool in landscape design research, so as to provide insight into the possibilities and limitations of using GIS in this capacity. The critical, information-oriented case of Stourhead landscape garden (Wiltshire, UK, an example of a designed landscape that covers the scope and remit of landscape architecture design, forms the heart of the study. The exploration of Stourhead by means of GIS can be understood as a plausibility probe. Here the case study is considered a form of ‘quasi-experiment’, testing the hypothesis and generating a learning process that constitutes a prerequisite for advanced understanding, while using an adjusted version of the framework for landscape design analysis by Steenbergen and Reh (2003. This is a theoretically informed analytical method based on the formal interpretation of the landscape architectonic composition addressing four landscape architectonic categories: the basic, the spatial, the symbolic and the programmatic form. This study includes new aspects to be

Firewood Resource Management in Different Landscapes in NW Patagonia

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Daniela V. Morales

2017-09-01

Full Text Available Ecosystems, their components, processes and functions are all subject to management by human populations, with the purpose of adapting the environments to make them more habitable and ensuring the availability and continuity of subsistence resources. Although a lot of work has been carried out on resources of alimentary or medicinal interest, little has been done on associating processes of domestication with firewood extraction, a practice considered to be destructive of the environment. In the arid steppe of NW Patagonia, inhabited and managed for different purposes for a long time by Mapuche-Tehuelche communities, the gathering of combustible plant species has up to the present time played a crucial role in cooking and heating, and work is required to achieve sustainability of this resource. In this study we evaluate whether environments with less landscape domestication are more intensively used for firewood gathering. Using an ethnobiological approach, information was obtained through participant observation, interviews and free listing. The data were examined using both qualitative and quantitative approaches. Twenty-eight firewood species are gathered, both native (75% and exotic (25%. The supply of firewood mainly depends on gathering from the domesticated (10 species, semi-domesticated (17 species and low human intervention landscapes (17 species. In contrast to our hypothesis, average use intensity is similar in all these landscapes despite their different levels of domestication. That is, the different areas are taken advantage of in a complementary manner in order to satisfy the domestic demand for firewood. Neither do biogeographic origin or utilitarian versatility of collected plants vary significantly between the different landscape levels of domestication. Our results show that human landscape domestication for the provision of firewood seems to be a socio-cultural resilient practice, and shed new light on the role of culture in

Industrious Landscaping

DEFF Research Database (Denmark)

Brichet, Nathalia Sofie; Hastrup, Frida

2018-01-01

This article has a twofold ambition. It offers a history of landscaping at Søby brown coal beds—a former mining site in western Denmark—and a methodological discussion of how to write such a study. Exploring this specific industrial landscape through a series of projects that have made different...... natural resources appear, we show that even what is recognized as resources shifts over time according to radically different and unpredictable agendas. This indicates that the Søby landscape is fundamentally volatile, as its resourcefulness has been seen interchangeably to shift between the brown coal...... business, inexpensive estates for practically savvy people, pasture for grazing, and recreational forest, among other things. We discuss these rifts in landscape history, motivated by what we refer to as industriousness, to show that, at sites such as Søby, both natural resources and historical...

Ten principles for a landscape approach to reconciling agriculture, conservation, and other competing land uses

Science.gov (United States)

Sayer, Jeffrey; Sunderland, Terry; Ghazoul, Jaboury; Pfund, Jean-Laurent; Sheil, Douglas; Meijaard, Erik; Venter, Michelle; Boedhihartono, Agni Klintuni; Day, Michael; Garcia, Claude; van Oosten, Cora; Buck, Louise E.

2013-01-01

“Landscape approaches” seek to provide tools and concepts for allocating and managing land to achieve social, economic, and environmental objectives in areas where agriculture, mining, and other productive land uses compete with environmental and biodiversity goals. Here we synthesize the current consensus on landscape approaches. This is based on published literature and a consensus-building process to define good practice and is validated by a survey of practitioners. We find the landscape approach has been refined in response to increasing societal concerns about environment and development tradeoffs. Notably, there has been a shift from conservation-orientated perspectives toward increasing integration of poverty alleviation goals. We provide 10 summary principles to support implementation of a landscape approach as it is currently interpreted. These principles emphasize adaptive management, stakeholder involvement, and multiple objectives. Various constraints are recognized, with institutional and governance concerns identified as the most severe obstacles to implementation. We discuss how these principles differ from more traditional sectoral and project-based approaches. Although no panacea, we see few alternatives that are likely to address landscape challenges more effectively than an approach circumscribed by the principles outlined here. PMID:23686581

Using Landscape metrics to analyze the landscape evolution under land abandonment

Science.gov (United States)

Pelorosso, Raffaele; Della Chiesa, Stefano; Gobattoni, Federica; Leone, Antonio

2010-05-01

The human actions and the human-linked land use changes are the main responsible of the present landscapes and vegetation patterns (Antrop, 2005; Pelorosso et al., 2009). Hence, revised concept of potential natural vegetation has been developed in landscape ecology. In fact, it cannot more be considered as the optimum for a certain landscape, but only as a general indication never widely reached. In particular Ingegnoli and Pignatti (2007) introduced the concept of fittest vegetation as "the most suitable or suited vegetation for the specific climate and geomorphic conditions, in a limited period of time and in a certain defined place with a particular range of incorporable disturbances (including man's) under natural or not natural conditions". Anthropic exploitation of land and its resources to obtain goods and services (Willemen et al, 2008) can be considered therefore the main cause of landscape change as an integrant part of nature, not external. The abandon of the land by farmers or other users it is one of the more felt problems for the marginal territories of Mediterranean basin. It is therefore caused by socio-economic changes of last decades and cause several impact on biodiversity (Geri et al. 2010) and hydro-geological assessment. A mountain landscape has however the capacity to provide goods like timber and services like aesthetic pleasure or regulation of water system. The necessity of a conservation strategy and the development of sustainable socio-economic management plan play a very important role in governing land and quality of life for people and ecosystems also for marginal territory. After a land abandonment, soil conditions and several climatic and orographic characteristic plus human disturbance affect the length of time required by secondary succession, throwing the establishment of vegetation with different association, structure and composition until a (stable or meta-stable) equilibrium is reached (Ingegnoli and Pignatti, 2007). In this

Annotation and Classification of CRISPR-Cas Systems.

Science.gov (United States)

Makarova, Kira S; Koonin, Eugene V

2015-01-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated proteins) is a prokaryotic adaptive immune system that is represented in most archaea and many bacteria. Among the currently known prokaryotic defense systems, the CRISPR-Cas genomic loci show unprecedented complexity and diversity. Classification of CRISPR-Cas variants that would capture their evolutionary relationships to the maximum possible extent is essential for comparative genomic and functional characterization of this theoretically and practically important system of adaptive immunity. To this end, a multipronged approach has been developed that combines phylogenetic analysis of the conserved Cas proteins with comparison of gene repertoires and arrangements in CRISPR-Cas loci. This approach led to the current classification of CRISPR-Cas systems into three distinct types and ten subtypes for each of which signature genes have been identified. Comparative genomic analysis of the CRISPR-Cas systems in new archaeal and bacterial genomes performed over the 3 years elapsed since the development of this classification makes it clear that new types and subtypes of CRISPR-Cas need to be introduced. Moreover, this classification system captures only part of the complexity of CRISPR-Cas organization and evolution, due to the intrinsic modularity and evolutionary mobility of these immunity systems, resulting in numerous recombinant variants. Moreover, most of the cas genes evolve rapidly, complicating the family assignment for many Cas proteins and the use of family profiles for the recognition of CRISPR-Cas subtype signatures. Further progress in the comparative analysis of CRISPR-Cas systems requires integration of the most sensitive sequence comparison tools, protein structure comparison, and refined approaches for comparison of gene neighborhoods.

Annotation and Classification of CRISPR-Cas Systems

Science.gov (United States)

Makarova, Kira S.; Koonin, Eugene V.

2018-01-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated proteins) is a prokaryotic adaptive immune system that is represented in most archaea and many bacteria. Among the currently known prokaryotic defense systems, the CRISPR-Cas genomic loci show unprecedented complexity and diversity. Classification of CRISPR-Cas variants that would capture their evolutionary relationships to the maximum possible extent is essential for comparative genomic and functional characterization of this theoretically and practically important system of adaptive immunity. To this end, a multipronged approach has been developed that combines phylogenetic analysis of the conserved Cas proteins with comparison of gene repertoires and arrangements in CRISPR-Cas loci. This approach led to the current classification of CRISPR-Cas systems into three distinct types and ten subtypes for each of which signature genes have been identified. Comparative genomic analysis of the CRISPR-Cas systems in new archaeal and bacterial genomes performed over the 3 years elapsed since the development of this classification makes it clear that new types and subtypes of CRISPR-Cas need to be introduced. Moreover, this classification system captures only part of the complexity of CRISPR-Cas organization and evolution, due to the intrinsic modularity and evolutionary mobility of these immunity systems, resulting in numerous recombinant variants. Moreover, most of the cas genes evolve rapidly, complicating the family assignment for many Cas proteins and the use of family profiles for the recognition of CRISPR-Cas subtype signatures. Further progress in the comparative analysis of CRISPR-Cas systems requires integration of the most sensitive sequence comparison tools, protein structure comparison, and refined approaches for comparison of gene neighborhoods. PMID:25981466

Selecting landscape metrics as indicators of spatial heterogeneity-A comparison among Greek landscapes

Science.gov (United States)

Plexida, Sofia G.; Sfougaris, Athanassios I.; Ispikoudis, Ioannis P.; Papanastasis, Vasilios P.

2014-02-01

This paper investigates the spatial heterogeneity of three landscapes along an altitudinal gradient and different human land use. The main aim was the identification of appropriate landscape indicators using different extents. ASTER image was used to create a land cover map consisting of three landscapes which differed in altitude and land use. A number of landscape metrics quantifying patch complexity, configuration, diversity and connectivity were derived from the thematic map at the landscape level. There were significant differences among the three landscapes regarding these four aspects of landscape heterogeneity. The analysis revealed a specific pattern of land use where lowlands are being increasingly utilized by humans (percentage of agricultural land = 65.84%) characterized by physical connectedness (high values of Patch Cohesion Index) and relatively simple geometries (low values of fractal dimension index). The landscape pattern of uplands was found to be highly diverse based upon the Shannon Diversity index. After selecting the scale (600 ha) where metrics values stabilized, it was shown that metrics were more correlated at the small scale of 60 ha. From the original 24 metrics, 14 individual metrics with high Spearman correlation coefficient and Variance Inflation Factor criterion were eliminated, leaving 10 representative metrics for subsequent analysis. Data reduction analysis showed that Patch Density, Area-Weighted Mean Fractal Dimension Index and Patch Cohesion Index are suitable to describe landscape patterns irrespective of the scale. A systematic screening of these metrics could enhance a deeper understanding of the results obtained by them and contribute to a sustainable landscape management of Mediterranean landscapes.

Explaining spatial variability in stream habitats using both natural and management-influenced landscape predictors

Science.gov (United States)

K.J. Anlauf; D.W. Jensen; K.M. Burnett; E.A. Steel; K. Christiansen; J.C. Firman; B.E. Feist; D.P. Larsen

2011-01-01

1. The distribution and composition of in-stream habitats are reflections of landscape scale geomorphic and climatic controls. Correspondingly, Pacific salmon (Oncorhynchus spp.) are largely adapted to and constrained by the quality and complexity of those in-stream habitat conditions. The degree to which lands have been fragmented and managed can...

Landscape Painting in Evaluation of Changes in Landscape

Czech Academy of Sciences Publication Activity Database

Lacina, Jan; Halas, Petr

2015-01-01

Roč. 8, č. 2 (2015), s. 60-68 ISSN 1803-2427 Institutional support: RVO:68145535 Keywords : landscape painting * landscape ecology * land-use changes * biodiversity Subject RIV: DE - Earth Magnetism, Geodesy, Geography http://www.degruyter.com/view/j/jlecol.2015.8.issue-2/jlecol-2015-0009/jlecol-2015-0009. xml

Urban Landscape Perspectives

Directory of Open Access Journals (Sweden)

Frederick Steiner

2014-03-01

Full Text Available Cities present significant opportunities for new landscape perspectives that can help inform conservation and development decisions. Early in the twenty-first century, the majority of the planet’s population became urban as more people lived in city-regions for the first time in our history. As the global population increases, so does this urbanization. The environmental challenges of population and urban growth are profound. Landscapes represent a synthesis of natural and cultural processes. Cities are certainly cultural phenomena. Historically, cities provided refuge from nature. The expanding field of urban ecology, coupled with landscape ecology, can enhance how the dual natural and cultural dimensions of landscapes in cities are understood. Furthermore, concepts such as ecosystem services and green infrastructure are proving useful for urban landscape planning and design. Examples from Dayton, Ohio; Brooklyn, New York; and Austin, Texas are presented.

Discourses across Scales on Forest Landscape Restoration

Directory of Open Access Journals (Sweden)

Sabine Reinecke

2018-02-01

Full Text Available Forest Landscape Restoration (FLR has recently received broad political support, e.g., under the Bonn Challenge. However, although the concept promises quadruple wins for humans, biodiversity as well as climate change mitigation and adaptation, it remains heavily underutilized in practice. Drawing on a social constructivist reading and a survey in different developing and developed countries, we elaborate on varying existing narratives about FLR at global and country level. Overall, we find that FLR understandings in different countries strongly resonate with the globally pursued idea of enhancing ecological and human well-being. In more detail, however, rural development and climate mitigation oriented motives are prioritized over aspects of species conservation or adaptation. Globally, strong emphasis is placed on collaborative processes empowering local actors. At country level, by contrast, these ideas regarding greater local authority are complemented with a techno-managerial notion of government control. Considering the potential power struggles that could be evoked from such dialectic expectations, we see it as a primary responsibility for global FLR processes to fully embrace the political dimension of FLR and to support conflict resolution and adaptive learning processes.

Data mining and model adaptation for the land use and land cover classification of a Worldview 2 image

Science.gov (United States)

Nascimento, L. C.; Cruz, C. B. M.; Souza, E. M. F. R.

2013-10-01

Forest fragmentation studies have increased since the last 3 decades. Land use and land cover maps (LULC) are important tools for this analysis, as well as other remote sensing techniques. The object oriented analysis classifies the image according to patterns as texture, color, shape, and context. However, there are many attributes to be analyzed, and data mining tools helped us to learn about them and to choose the best ones. In this way, the aim of this paper is to describe data mining techniques and results of a heterogeneous area, as the municipality of Silva Jardim, Rio de Janeiro, Brazil. The municipality has forest, urban areas, pastures, water bodies, agriculture and also some shadows as objects to be represented. Worldview 2 satellite image from 2010 was used and LULC classification was processed using the values that data mining software has provided according to the J48 method. Afterwards, this classification was analyzed, and the verification was made by the confusion matrix, being possible to evaluate the accuracy (58,89%). The best results were in classes "water" and "forest" which have more homogenous reflectance. Because of that, the model has been adapted, in order to create a model for the most homogeneous classes. As result, 2 new classes were created, some values and some attributes changed, and others added. In the end, the accuracy was 89,33%. It is important to highlight this is not a conclusive paper; there are still many steps to develop in highly heterogeneous surfaces.

Incorporating Bioenergy in Sustainable Landscape Designs Workshop Two: Agricultural Landscapes

Energy Technology Data Exchange (ETDEWEB)

None

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.

Selection towards different adaptive optima drove the early diversification of locomotor phenotypes in the radiation of Neotropical geophagine cichlids.

Science.gov (United States)

Astudillo-Clavijo, Viviana; Arbour, Jessica H; López-Fernández, Hernán

2015-05-01

Simpson envisaged a conceptual model of adaptive radiation in which lineages diversify into "adaptive zones" within a macroevolutionary adaptive landscape. However, only a handful of studies have empirically investigated this adaptive landscape and its consequences for our interpretation of the underlying mechanisms of phenotypic evolution. In fish radiations the evolution of locomotor phenotypes may represent an important dimension of ecomorphological diversification given the implications of locomotion for feeding and habitat use. Neotropical geophagine cichlids represent a newly identified adaptive radiation and provide a useful system for studying patterns of locomotor diversification and the implications of selective constraints on phenotypic divergence in general. We use multivariate ordination, models of phenotypic evolution and posterior predictive approaches to investigate the macroevolutionary adaptive landscape and test for evidence of early divergence of locomotor phenotypes in Geophagini. The evolution of locomotor phenotypes was characterized by selection towards at least two distinct adaptive peaks and the early divergence of modern morphological disparity. One adaptive peak included the benthic and epibenthic invertivores and was characterized by fishes with deep, laterally compressed bodies that optimize precise, slow-swimming manoeuvres. The second adaptive peak resulted from a shift in adaptive optima in the species-rich ram-feeding/rheophilic Crenicichla-Teleocichla clade and was characterized by species with streamlined bodies that optimize fast starts and rapid manoeuvres. Evolutionary models and posterior predictive approaches favoured an early shift to a new adaptive peak over decreasing rates of evolution as the underlying process driving the early divergence of locomotor phenotypes. The influence of multiple adaptive peaks on the divergence of locomotor phenotypes in Geophagini is compatible with the expectations of an ecologically driven

Participatory Planning, Monitoring and Evaluation of Multi-Stakeholder Platforms in Integrated Landscape Initiatives.

Science.gov (United States)

Kusters, Koen; Buck, Louise; de Graaf, Maartje; Minang, Peter; van Oosten, Cora; Zagt, Roderick

2017-03-21

Integrated landscape initiatives typically aim to strengthen landscape governance by developing and facilitating multi-stakeholder platforms. These are institutional coordination mechanisms that enable discussions, negotiations, and joint planning between stakeholders from various sectors in a given landscape. Multi-stakeholder platforms tend to involve complex processes with diverse actors, whose objectives and focus may be subjected to periodic re-evaluation, revision or reform. In this article we propose a participatory method to aid planning, monitoring, and evaluation of such platforms, and we report on experiences from piloting the method in Ghana and Indonesia. The method is comprised of three components. The first can be used to look ahead, identifying priorities for future multi-stakeholder collaboration in the landscape. It is based on the identification of four aspirations that are common across multi-stakeholder platforms in integrated landscape initiatives. The second can be used to look inward. It focuses on the processes within an existing multi-stakeholder platform in order to identify areas for possible improvement. The third can be used to look back, identifying the main outcomes of an existing platform and comparing them to the original objectives. The three components can be implemented together or separately. They can be used to inform planning and adaptive management of the platform, as well as to demonstrate performance and inform the design of new interventions.

Transgenerational stress-adaption: an opportunity for ecological epigenetics.

Science.gov (United States)

Weinhold, Arne

2018-01-01

In the recent years, there has been considerable interest to investigate the adaptive transgenerational plasticity of plants and how a "stress memory" can be transmitted to the following generation. Although, increasing evidence suggests that transgenerational adaptive responses have widespread ecological relevance, the underlying epigenetic processes have rarely been elucidated. On the other hand, model plant species have been deeply investigated in their genome-wide methylation landscape without connecting this to the ecological reality of the plant. What we need is the combination of an ecological understanding which plant species would benefit from transgenerational epigenetic stress-adaption in their natural habitat, combined with a deeper molecular analysis of non-model organisms. Only such interdisciplinary linkage in an ecological epigenetic study could unravel the full potential that epigenetics could play for the transgenerational stress-adaption of plants.

URBAN LANDSCAPE QUALITY AND FACTORS THAT HAVE INFLUENCE ON LANDSCAPE QUALITY IN LATGALE REGION

OpenAIRE

Matisovs, Ivars

2005-01-01

The paper deals with urban landscape individualities in the cities and towns of Latgale region. Also show facilities and methods of integrated assessment of urban landscape quality. Article provides information about specifics of urban landscape and factors, that have influence on landscape quality. The paper presents the results of Daugavpils and Rēzekne urban landscape quality complex assessment, that have been realised in 2003- 2005. This results don’t establish significant disparities bet...

Mapping the Mayo-Portland adaptability inventory to the international classification of functioning, disability and health.

Science.gov (United States)

Lexell, Jan; Malec, James F; Jacobsson, Lars J

2012-01-01

To examine the contents of the Mayo-Portland Adaptability Inventory (MPAI-4) by mapping it to the International Classification of Functioning, Disability and Health (ICF). Each of the 30 scoreable items in the MPAI-4 was mapped to the most precise ICF categories. All 30 items could be mapped to components and categories in the ICF. A total of 88 meaningful concepts were identified. There were, on average, 2.9 meaningful concepts per item, and 65% of all concepts could be mapped. Items in the Ability and Adjustment subscales mapped to categories in both the Body Functions and Activity/Participation components of the ICF, whereas all except 1 in the Participation subscale were to categories in the Activity/Participation component. The items could also be mapped to 34 (13%) of the 258 Environmental Factors in the ICF. This mapping provides better definition through more concrete examples (as listed in the ICF) of the types of body functions, activities, and participation indicators that are represented by the 30 scoreable MPAI-4 items. This may assist users throughout the world in understanding the intent of each item, and support further development and the possibility to report results in the form of an ICF categorical profile, making it universally interpretable.

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

Science.gov (United States)

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

MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA

Directory of Open Access Journals (Sweden)

M. Soheili Majd

2012-09-01

Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.

Applying information network analysis to fire-prone landscapes: implications for community resilience

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Derric B. Jacobs

2017-03-01

Full Text Available Resilient communities promote trust, have well-developed networks, and can adapt to change. For rural communities in fire-prone landscapes, current resilience strategies may prove insufficient in light of increasing wildfire risks due to climate change. It is argued that, given the complexity of climate change, adaptations are best addressed at local levels where specific social, cultural, political, and economic conditions are matched with local risks and opportunities. Despite the importance of social networks as key attributes of community resilience, research using social network analysis on coupled human and natural systems is scarce. Furthermore, the extent to which local communities in fire-prone areas understand climate change risks, accept the likelihood of potential changes, and have the capacity to develop collaborative mitigation strategies is underexamined, yet these factors are imperative to community resiliency. We apply a social network framework to examine information networks that affect perceptions of wildfire and climate change in Central Oregon. Data were collected using a mailed questionnaire. Analysis focused on the residents' information networks that are used to gain awareness of governmental activities and measures of community social capital. A two-mode network analysis was used to uncover information exchanges. Results suggest that the general public develops perceptions about climate change based on complex social and cultural systems rather than as patrons of scientific inquiry and understanding. It appears that perceptions about climate change itself may not be the limiting factor in these communities' adaptive capacity, but rather how they perceive local risks. We provide a novel methodological approach in understanding rural community adaptation and resilience in fire-prone landscapes and offer a framework for future studies.

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery. Caribbean Journal of Science. 44(2):175-198.

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E.H. Helmer; T.A. Kennaway; D.H. Pedreros; M.L. Clark; H. Marcano-Vega; L.L. Tieszen; S.R. Schill; C.M.S. Carrington

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius...

Odor Classification using Agent Technology

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Sigeru OMATU

2014-03-01

Full Text Available In order to measure and classify odors, Quartz Crystal Microbalance (QCM can be used. In the present study, seven QCM sensors and three different odors are used. The system has been developed as a virtual organization of agents using an agent platform called PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents. This is a platform for developing open multi-agent systems, specifically those including organizational aspects. The main reason for the use of agents is the scalability of the platform, i.e. the way in which it models the services. The system models functionalities as services inside the agents, or as Service Oriented Approach (SOA architecture compliant services using Web Services. This way the adaptation of the odor classification systems with new algorithms, tools and classification techniques is allowed.

Lines of landscape organisation

DEFF Research Database (Denmark)

Løvschal, Mette

2015-01-01

This paper offers a landscape analysis of the earliest linear landscape boundaries on Skovbjerg Moraine, Denmark, during the first millennium BC. Using Delaunay triangulation as well as classic distribution analyses, it demonstrates that landscape boundaries articulated already established use-pa...

Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

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Xiaolong Liu

2015-01-01

Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that

A novel Neuro-fuzzy classification technique for data mining

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Soumadip Ghosh

2014-11-01

Full Text Available In our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The inputs to the Neuro-fuzzy classification system were fuzzified by applying generalized bell-shaped membership function. The proposed method utilized a fuzzification matrix in which the input patterns were associated with a degree of membership to different classes. Based on the value of degree of membership a pattern would be attributed to a specific category or class. We applied our method to ten benchmark data sets from the UCI machine learning repository for classification. Our objective was to analyze the proposed method and, therefore compare its performance with two powerful supervised classification algorithms Radial Basis Function Neural Network (RBFNN and Adaptive Neuro-fuzzy Inference System (ANFIS. We assessed the performance of these classification methods in terms of different performance measures such as accuracy, root-mean-square error, kappa statistic, true positive rate, false positive rate, precision, recall, and f-measure. In every aspect the proposed method proved to be superior to RBFNN and ANFIS algorithms.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing.

Science.gov (United States)

O'Connell, Jerome; Bradter, Ute; Benton, Tim G

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer ( Emberiza citronella ), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m 2 . The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

Science.gov (United States)

O'Connell, Jerome; Bradter, Ute; Benton, Tim G.

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ˜22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

An Agent-Based Assessment of Land Use and Ecosystem Changes in Traditional Agricultural Landscape of Portugal

NARCIS (Netherlands)

Acosta, L.; Rounsevell, M.D.A.; Bakker, M.M.; Doorn, van A.M.; Gómez-Delgado, M.; Delgado, M.

2014-01-01

This paper presents an assessment of land use changes and their impacts on the ecosystem in the Montado, a traditional agricultural landscape of Portugal in response to global environmental change. The assessment uses an agent- based model (ABM) of the adaptive decisions of farmers to simulate the

Management and development of land in the name of the Green Economy: planning, landscape, efficiency, biodiversity

Science.gov (United States)

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.

Beyond the conventional: meeting the challenges of landscape governance within the European Landscape Convention?

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Scott, Alister

2011-10-01

Academics and policy makers seeking to deconstruct landscape face major challenges conceptually, methodologically and institutionally. The meaning(s), identity(ies) and management of landscape are controversial and contested. The European Landscape Convention provides an opportunity for action and change set within new governance agendas addressing interdisciplinarity and spatial planning. This paper critically reviews the complex web of conceptual and methodological frameworks that characterise landscape planning and management and then focuses on emerging landscape governance in Scotland within a mixed method approach involving policy analyses, semi-structured interviews and best practice case studies. Using Dower's (2008) criteria from the Articles of the European Landscape Convention, the results show that whilst some progress has been made in landscape policy and practice, largely through the actions of key individuals and champions, there are significant institutional hurdles and resource limitations to overcome. The need to mainstream positive landscape outcomes requires a significant culture change where a one-size-fits-all approach does not work. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mapping landscape units in Galicia (Spain: A first step for assessment and management?

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Corbelle-Rico Eduardo

2017-12-01

Full Text Available In the beginning of 2015, the Regional Administration of Galicia (NW Spain set the requirements for a map of landscape units: it had to be produced in less than 3 months, it should cover the whole territory of the region (29,574 km², and it should be useful for management at a scale of 1:25,000. With these objectives in mind, we pro- posed a semiautomatic mapping methodology entirely based on the use of free software (GRASS GIS and already available cartographic information. Semi-automatic classification of different land-use patterns was at the heart of the proposed process. Consultation with experts of different academic background took place along the project. This consultation process allowed to identify both problems and opportunities. As it could be expected, the diverse epistemic community represented by the expert panel implied that one of the main challenges was to reach consensus on the understanding of the concept of landscape and the decisions leading to the mapping methodology proposed in this paper. This initiated a very interesting debate that, in our view, was centred around three main issues: the approach to the landscape, the purpose of the mapping exercise, and the ability to include subjectivity into the analysis.

Why Landscape Beauty Matters

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Angelika Krebs

2014-11-01

Full Text Available This philosophical paper explores the aesthetic argument for landscape conservation. The main claim is that the experience of beautiful landscapes is an essential part of the good human life. Beautiful landscapes make us feel at home in the world. Their great and irreplaceable value lies therein. To establish this claim, the concepts of landscape and “Stimmung” are clarified. It is shown how “Stimmung” (in the sense of mood is infused into landscape (as atmosphere and how we respond to it aesthetically. We respond by resonating or feeling at home. The paper ends by indicating how art can help us to better appreciate landscape beauty. This is done by way of an example from contemporary nature poetry, Michael Donhauser’s Variationen in Prosa, which begins with “Und was da war, es nahm uns an” (“And what was there accepted us”.

Fifty-year spatiotemporal analysis of landscape changes in the Mont Saint-Hilaire UNESCO Biosphere Reserve (Quebec, Canada).

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Béliveau, Marc; Germain, Daniel; Ianăş, Ana-Neli

2017-05-01

Diachronic analysis with a GIS-based classification of land-use changes based on aerial photographs, orthophotos, topographic maps, geotechnical reports, urban plans, and using landscape metrics has permitted insight into the driving forces responsible for landscape fragmentation in the Mont Saint-Hilaire (MSH) Biosphere Reserve over the period 1958-2015. Although the occurrence of exogenous factors, such as extreme weather and fires, can have a significant influence on the fragmentation of the territory in time and space, the accelerated development of the built environment (+470%) is nevertheless found to be primarily responsible for landscape fragmentation and the loss of areas formerly occupied by orchards, agriculture, and woodlands. The landscape metrics used corroborate these results, with a simplification of the shape of polygons, and once again reveal the difficulties of harmonizing different land uses. MSH has become somewhat of a forest island in a sea of residential development and agriculture. To counter this isolation of fragmented habitat components, forest corridors have been proposed and developed for the Biosphere Reserve and particularly for the core area. Two corridors, to the north and south, are used to connect the protected area and other wooded areas at the regional scale, in order to promote genetic exchange between populations of various species. In that regard, the forest buffer zone around the hill continues to play a key role and has great ecological value for species and ecological preservation and conservation. However, appropriate management and landscape preservation actions should recognize and focus on landscape composition and the associated geographical configuration.

Legible landscapes: the use of narratives in landscape design for leisure and tourism in Dutch cultural landscapes.

NARCIS (Netherlands)

Brinkhuijsen, M.

2007-01-01

Nowadays, leisure and tourism have become significant factors in rural development, which is manifest in the ‘commodification’ of landscapes. However, leisure and tourist markets are very competitive and consumers increasingly demand high quality, unique and memorable experiences. Landscape

Migrant decision-making in a frontier landscape

Science.gov (United States)

Salerno, Jonathan

2016-04-01

Across the tropics, rural farmers and livestock keepers use mobility as an adaptive livelihood strategy. Continued migration to and within frontier areas is widely viewed as a driver of environmental decline and biodiversity loss. Recent scholarship advances our understanding of migration decision-making in the context of changing climate and environments, and in doing so it highlights the variation in migration responses to primarily economic and environmental factors. Building on these insights, this letter investigates past and future migration decisions in a frontier landscape of Tanzania, East Africa. Combining field observations and household data within a multilevel modeling framework, the letter analyzes the explicit importance of social factors relative to economic and environmental factors in driving decisions to migrate or remain. Results indeed suggest that local community ties and non-local social networks drive both immobility and anticipated migration, respectively. In addition, positive interactions with local protected natural resource areas promote longer-term residence. Findings shed new light on how frontier areas transition to human dominated landscapes. This highlights critical links between migration behavior and the conservation of biodiversity and management of natural resources, as well as how migrants evolve to become integrated into communities.

Identification Of Minangkabau Landscape Characters

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Asrina, M.; Gunawan, A.; Aris, Munandar

2017-10-01

Minangkabau is one of cultures in indonesia which occupies landscape intact. Landscape of Minangkabau have a very close relationship with the culture of the people. Uniqueness of Minangkabau culture and landscape forming an inseparable characterunity. The landscape is necessarily identified to know the inherent landscape characters. The objective of this study was to identify the character of the Minangkabau landscape characterizes its uniqueness. The study was conducted by using descriptive method comprised literature review and field observasion. Observed the landscape characters comprised two main features, they were major and minor features. Indetification of the features was conducted in two original areas (darek) of the Minangkabau traditional society. The research results showed that major features or natural features of the landscape were predominantly landform, landcover, and hidrology. All luhak (districts) of Minangkabau showed similar main features such as hill, canyon, lake, valley, and forest. The existence of natural features such as hills, canyon and valleys characterizes the nature of minangkabau landscape. Minor features formed by Minangkabau cultural society were agricultural land and settlement. Rumah gadang (big house) is one of famous minor features characterizes the Minangkabau culture. In addition, several historical artefacts of building and others structure may strengthen uniqueness of the Minangkabau landscape character, such as The royal palace, inscription, and tunnels.

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

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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 ...

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

Science.gov (United States)

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.

Adaptive skin detection based on online training

Science.gov (United States)

Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

2007-11-01

Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

A novel approach for classification of abnormalities in digitized ...

Indian Academy of Sciences (India)

Feature extraction is an important process for the overall system performance in classification. The objective of this article is to reveal the effectiveness of texture feature analysis for detecting the abnormalities in digitized mammograms using Self Adaptive Resource Allocation Network (SRAN) classifier. Thus, we proposed a ...

The Sigiriya Royal Gardens. Analysis of the Landscape Architectonic Composition

Directory of Open Access Journals (Sweden)

Jude Nilan Cooray

2017-11-01

Full Text Available Besides the efforts that are of descriptive and celebrative nature, studies related to Sri Lanka’s historical built heritage are largely to view material remains in historical, sociological, socio-historical and semiological perspectives. But there is hardly any serious attempt to view such material remains from a technical-analytical approach to understand the compositional aspects of their designs. The 5th century AC royal complex at Sigiriya is no exception in this regard. The enormous wealth of information and the unearthed material remains during more than hundred years of field-based research by several generations of archaeologists at Sigiriya provide ideal opportunity for such an analysis. The present study is, therefore, to fill the gap in research related to Sri Lanka’s historical built heritage in general and to Sigiriya in particular. Therefore the present research attempts to read Sigiriya as a landscape architectonic design to expose its architectonic composition and design instruments. The study which is approached from a technical-analytical point of view follows a methodological framework that is developed at the Landscape Design Department of the Faculty of Architecture at Delft University of Technology. The study reveals that the architectonic design of Sigiriya constitutes multiple design layers and multiple layers of significance with material-spatial-metaphorical-functional coherence, and that it has both general and unique landscape architectonic elements, aspects, characteristics and qualities. The richness of its composition also enables to identify the landscape architectural value of the Sigiriya, which will help re-shape the policies related to conservation and presentation of Sigiriya as a heritage site as well as the protection and management as a green monument. The positive results of the study also underline that the methodology adapted in this research has devised a framework for the study of other examples

A General Model for Estimating Macroevolutionary Landscapes.

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Boucher, Florian C; Démery, Vincent; Conti, Elena; Harmon, Luke J; Uyeda, Josef

2018-03-01

The evolution of quantitative characters over long timescales is often studied using stochastic diffusion models. The current toolbox available to students of macroevolution is however limited to two main models: Brownian motion and the Ornstein-Uhlenbeck process, plus some of their extensions. Here, we present a very general model for inferring the dynamics of quantitative characters evolving under both random diffusion and deterministic forces of any possible shape and strength, which can accommodate interesting evolutionary scenarios like directional trends, disruptive selection, or macroevolutionary landscapes with multiple peaks. This model is based on a general partial differential equation widely used in statistical mechanics: the Fokker-Planck equation, also known in population genetics as the Kolmogorov forward equation. We thus call the model FPK, for Fokker-Planck-Kolmogorov. We first explain how this model can be used to describe macroevolutionary landscapes over which quantitative traits evolve and, more importantly, we detail how it can be fitted to empirical data. Using simulations, we show that the model has good behavior both in terms of discrimination from alternative models and in terms of parameter inference. We provide R code to fit the model to empirical data using either maximum-likelihood or Bayesian estimation, and illustrate the use of this code with two empirical examples of body mass evolution in mammals. FPK should greatly expand the set of macroevolutionary scenarios that can be studied since it opens the way to estimating macroevolutionary landscapes of any conceivable shape. [Adaptation; bounds; diffusion; FPK model; macroevolution; maximum-likelihood estimation; MCMC methods; phylogenetic comparative data; selection.].

History and Local Management of a Biodiversity-Rich, Urban Cultural Landscape

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Stephan Barthel

2005-12-01

Full Text Available Urban green spaces provide socially valuable ecosystem services. Through an historical analysis of the development of the National Urban Park (NUP of Stockholm, we illustrate how the co-evolutionary process of humans and nature has resulted in the high level of biological diversity and associated recreational services found in the park. The ecological values of the area are generated in the cultural landscape. External pressures resulting in urban sprawl in the Stockholm metropolitan region increasingly challenge the capacity of the NUP to continue to generate valuable ecosystem services. Setting aside protected areas, without accounting for the role of human stewardship of the cultural landscape, will most likely fail. In a social inventory of the area, we identify 69 local user and interest groups currently involved in the NUP area. Of these, 25 are local stewardship associations that have a direct role in managing habitats within the park that sustain such services as recreational landscapes, seed dispersal, and pollination. We propose that incentives should be created to widen the current biodiversity management paradigm, and actively engage local stewardship associations in adaptive co-management processes of the park and surrounding green spaces.

[Object-oriented remote sensing image classification in epidemiological studies of visceral leishmaniasis in urban areas].

Science.gov (United States)

Almeida, Andréa Sobral de; Werneck, Guilherme Loureiro; Resendes, Ana Paula da Costa

2014-08-01

This study explored the use of object-oriented classification of remote sensing imagery in epidemiological studies of visceral leishmaniasis (VL) in urban areas. To obtain temperature and environmental information, an object-oriented classification approach was applied to Landsat 5 TM scenes from the city of Teresina, Piauí State, Brazil. For 1993-1996, VL incidence rates correlated positively with census tracts covered by dense vegetation, grass/pasture, and bare soil and negatively with areas covered by water and densely populated areas. In 2001-2006, positive correlations were found with dense vegetation, grass/pasture, bare soil, and densely populated areas and negative correlations with occupied urban areas with some vegetation. Land surface temperature correlated negatively with VL incidence in both periods. Object-oriented classification can be useful to characterize landscape features associated with VL in urban areas and to help identify risk areas in order to prioritize interventions.

Integrating landscape ecology and geoinformatics to decipher landscape dynamics for regional planning.

Science.gov (United States)

Dikou, Angela; Papapanagiotou, Evangelos; Troumbis, Andreas

2011-09-01

We used remote sensing and GIS in conjunction with multivariate statistical methods to: (i) quantify landscape composition (land cover types) and configuration (patch density, diversity, fractal dimension, contagion) for five coastal watersheds of Kalloni gulf, Lesvos Island, Greece, in 1945, 1960, 1971, 1990 and 2002/2003, (ii) evaluate the relative importance of physical (slope, geologic substrate, stream order) and human (road network, population density) variables on landscape composition and configuration, and (iii) characterize processes that led to land cover changes through land cover transitions between these five successive periods in time. Distributions of land cover types did not differ among the five time periods at the five watersheds studied because the largest cumulative changes between 1945 and 2002/2003 did not take place at dominant land cover types. Landscape composition related primarily to the physical attributes of the landscape. Nevertheless, increase in population density and the road network were found to increase heterogeneity of the landscape mosaic (patchiness), complexity of patch shape (fractal dimension), and patch disaggregation (contagion). Increase in road network was also found to increase landscape diversity due to the creation of new patches. The main processes involved in land cover changes were plough-land abandonment and ecological succession. Landscape dynamics during the last 50 years corroborate the ecotouristic-agrotouristic model for regional development to reverse trends in agricultural land abandonment and human population decline and when combined with hypothetical regulatory approaches could predict how this landscape could develop in the future, thus, providing a valuable tool to regional planning.

Condensed landscape experience

DEFF Research Database (Denmark)

Earon, Ofri

2011-01-01

demands, quality of space, mixture of functions, urban complexity, public life and cultural heritage. In order to launch such an approach, an understanding of the spatial, social and environmental significance of a radical re-thinking of relationships between architecture and landscape is necessary...... is becoming a standard in contemporary architecture. Merging architecture and landscape has turned into a principle for an ecological / sustainable architecture. Yet, my aspiration is to achieve a wider interaction involving an application of a wider range of perspectives, such as: urban identity, social......‘Re-thinking interaction between landscape and urban buildings’ participates in an interdisciplinary discourse about the theoretical and practical advantages of openly juxtaposing landscape and architecture without having one more advanced in importance. Recently, the greenification of buildings...

Soils in an agricultural landscape of Jokioinen, south-western Finland

Directory of Open Access Journals (Sweden)

M. YLI-HALLA

2008-12-01

Full Text Available Eleven pedons in an agricultural landscape at elevations 80-130 m above sea level in Jokioinen, south-western Finland were investigated and classified according to Soil Taxonomy, the FAO-Unesco system (FAO, and the World Reference Base for Soil Resources system (WRB. The soils were related to geomorphology of the landscape which is characterized by clayey fields and forested bedrock high areas covered with glacial till. A Spodosol/Podzol was found in a coarse-sandy soil in an esker while the sandy loam in a bedrock high area soils did not have an E horizon. A man-made mollic epipedon was found in a cultivated soil which had a sandy plow layer while clayey plow layers were ochric epipedons. Cambic horizons, identified by structure and redox concentrations, were common in cultivated soils. In a heavy clay soil, small slickensides and wedge-shaped aggregates, i.e., vertic characteristics, were found. Histosols occurred in local topographic depressions irrespective of the absolute elevation. According to the three classification systems, the following catenas are recognized: Haplocryods - Dystro/Eutrocryepts -Haplocryolls - Cryaquepts - Cryosaprists (Soil Taxonomy, Podzols - Regosols - Cambisols - Histosols (FAO-Unesco, and Podzols - Cambisols - Phaeozems - Gleysols - Histosols (WRB.;

Linking biogeomorphic feedbacks from ecosystem engineer to landscape scale: a panarchy approach

Science.gov (United States)

Eichel, Jana

2017-04-01

Scale is a fundamental concept in both ecology and geomorphology. Therefore, scale-based approaches are a valuable tool to bridge the disciplines and improve the understanding of feedbacks between geomorphic processes, landforms, material and organisms and ecological processes in biogeomorphology. Yet, linkages between biogeomorphic feedbacks on different scales, e.g. between ecosystem engineering and landscape scale patterns and dynamics, are not well understood. A panarchy approach sensu Holling et al. (2002) can help to close this research gap and explain how structure and function are created in biogeomorphic ecosystems. Based on results from previous biogeomorphic research in Turtmann glacier foreland (Switzerland; Eichel, 2017; Eichel et al. 2013, 2016), a panarchy concept is presented for lateral moraine slope biogeomorphic ecosystems. It depicts biogeomorphic feedbacks on different spatiotemporal scales as a set of nested adaptive cycles and links them by 'remember' and 'revolt' connections. On a small scale (cm2 - m2; seconds to years), the life cycle of the ecosystem engineer Dryas octopetala L. is considered as an adaptive cycle. Biogeomorphic succession within patches created by geomorphic processes represents an intermediate scale adaptive cycle (m2 - ha, years to decades), while geomorphic and ecologic pattern development at a landscape scale (ha - km2, decades to centuries) can be illustrated by an adaptive cycle of ‚biogeomorphic patch dynamics' (Eichel, 2017). In the panarchy, revolt connections link the smaller scale adaptive cycles to larger scale cycles: on lateral moraine slopes, the development of ecosystem engineer biomass and cover controls the engineering threshold of the biogeomorphic feedback window (Eichel et al., 2016) and therefore the onset of the biogeomorphic phase during biogeomorphic succession. In this phase, engineer patches and biogeomorphic structures can be created in the patch mosaic of the landscape. Remember connections

Analysis of landscape patterns and their relationship with oak (Quercus Humboldtii Bonpl.) regeneration in the municipality of Popayan, Cauca

International Nuclear Information System (INIS)

Cabezas Gaviria Alexander; Ospina Montealegre Roman

2010-01-01

Landscape patterns were determined for three different areas having oak populations in the Popayan municipality (Clarete, Rejoya and Pisoje). Two Landsat images from different years and polygons with areas equal or greater than 1.5 hectares were used for land use classification. Patch Analysis software was used in order to determine quantitative variables. Structure description included: number of patches, mean patch size, mean patch index, mean patch fractal dimension and mean perimeter-area ratio. Dispersion and fragmentation were evaluated with the three indexes: Mean Nearest Neighbor Distance, Mean Proximity Index and Interspersion Juxtaposition Index. Community variables included: basal area, terrain slope, light percentage and regeneration density, and were measured in an area of 3600 m2 for each landscape. Landscape and community information were analyzed using principal component analysis (PCA). The first two components explained 91.4% of data variability; they were determined mostly by landscape variables than community factors. Correlation analysis and the Kruskal-Wallis test showed that the variable of major importance regarding oak tree regeneration were the Neighbor Distance in secondary forest patches, the Mean Proximity Index in oak tree forest patches and the Juxtaposition Index in patches of planted forests.

Visualization of landscape changes and threatening environmental processes using a digital landscape model

International Nuclear Information System (INIS)

Svatonova, H; Rybansky, M

2014-01-01

Visualizations supported by new geoinformation technologies prove to be appropriate tools for presenting and sharing the research results by professional and general public. The object of the research was to evaluate the benefits of visualizations for the nonexpert users. The subject of evaluation was: the success rate of interpreting the information; forming of a realistic idea of the unknown landscape; and the preference of the users during selection of the appropriate visualization for the purpose of solving the task. The tasks concerned: assessing the current situation and changes of the landscape; assessing the erosion in the landscape; and the ways of their visualizing. To prepare and process the landscape visualizations, it was necessary to select areas that allow tracking of land use changes and representative environmental processes. Then the digital landscape model was created and a number of visualizations were generated. The results of visualization testing show that the users prefer maps to orthophotos, they are able to formulate correct statements concerning the landscape with the help of visualizations, and that the simulated fly throughs represent a very suitable tool supporting formation of a realistic ideas about the landscape

Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model.

Science.gov (United States)

Brunker, K; Hampson, K; Horton, D L; Biek, R

2012-12-01

Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

Landscape genetics and limiting factors

Science.gov (United States)

Samuel A. Cushman; Andrew J. Shirk; Erin L. Landguth

2013-01-01

Population connectivity is mediated by the movement of organisms or propagules through landscapes. However, little is known about how variation in the pattern of landscape mosaics affects the detectability of landscape genetic relationships. The goal of this paper is to explore the impacts of limiting factors on landscape genetic processes using simulation...

Testing evolutionary hypotheses for phenotypic divergence using landscape genetics.

Science.gov (United States)

Funk, W Chris; Murphy, Melanie A

2010-02-01

Understanding the evolutionary causes of phenotypic variation among populations has long been a central theme in evolutionary biology. Several factors can influence phenotypic divergence, including geographic isolation, genetic drift, divergent natural or sexual selection, and phenotypic plasticity. But the relative importance of these factors in generating phenotypic divergence in nature is still a tantalizing and unresolved problem in evolutionary biology. The origin and maintenance of phenotypic divergence is also at the root of many ongoing debates in evolutionary biology, such as the extent to which gene flow constrains adaptive divergence (Garant et al. 2007) and the relative importance of genetic drift, natural selection, and sexual selection in initiating reproductive isolation and speciation (Coyne & Orr 2004). In this issue, Wang & Summers (2010) test the causes of one of the most fantastic examples of phenotypic divergence in nature: colour pattern divergence among populations of the strawberry poison frog (Dendrobates pumilio) in Panama and Costa Rica (Fig. 1). This study provides a beautiful example of the use of the emerging field of landscape genetics to differentiate among hypotheses for phenotypic divergence. Using landscape genetic analyses, Wang & Summers were able to reject the hypotheses that colour pattern divergence is due to isolation-by-distance (IBD) or landscape resistance. Instead, the hypothesis left standing is that colour divergence is due to divergent selection, in turn driving reproductive isolation among populations with different colour morphs. More generally, this study provides a wonderful example of how the emerging field of landscape genetics, which has primarily been applied to questions in conservation and ecology, now plays an essential role in evolutionary research.

Condensed landscape experience

DEFF Research Database (Denmark)

Earon, Ofri

2011-01-01

‘Re-thinking interaction between landscape and urban buildings’ participates in an interdisciplinary discourse about the theoretical and practical advantages of openly juxtaposing landscape and architecture without having one more advanced in importance. Recently, the greenification of buildings...... demands, quality of space, mixture of functions, urban complexity, public life and cultural heritage. In order to launch such an approach, an understanding of the spatial, social and environmental significance of a radical re-thinking of relationships between architecture and landscape is necessary...

Slope stability probability classification, Waikato Coal Measures, New Zealand

Energy Technology Data Exchange (ETDEWEB)

Lindsay, P.; Gillard, G.R.; Moore, T.A. [CRL Energy, PO Box 29-415, Christchurch (New Zealand); Campbell, R.N.; Fergusson, D.A. [Solid Energy North, Private Bag 502, Huntly (New Zealand)

2001-01-01

Ferm classified lithological units have been identified and described in the Waikato Coal Measures in open pits in the Waikato coal region. These lithological units have been classified geotechnically by mechanical tests and discontinuity measurements. Using these measurements slope stability probability classifications (SSPC) have been quantified based on an adaptation of Hack's [Slope Stability Probability Classification, ITC Delft Publication, Enschede, Netherlands, vol. 43, 1998, 273 pp.] SSPC system, which places less influence on rock quality designation and unconfined compressive strength than previous slope/rock mass rating systems. The Hack weathering susceptibility rating has been modified by using chemical index of alteration values determined from XRF major element analyses. Slaking is an important parameter in slope stability in the Waikato Coal Measures lithologies and hence, a non-subjective method of assessing slaking in relation to the chemical index of alteration has been introduced. Another major component of this adapted SSPC system is the inclusion of rock moisture content effects on slope stability. The main modifications of Hack's SSPC system are the introduction of rock intact strength derived from the modified Mohr-Coulomb failure criterion, which has been adapted for varying moisture content, weathering state and confining pressure. It is suggested that the subjectivity in assessing intact rock strength within broad bands in the initial SSPC system is a major weakness of the initial system. Initial results indicate a close relationship between rock mass strength values, calculated from rock mass friction angles and rock mass cohesion values derived from two established rock mass classification methods (modified Hoek-Brown failure criteria and MRMR) and the adapted SSPC system. The advantage of the modified SSPC system is that slope stability probabilities based on discontinuity-independent and discontinuity-dependent data and a

Geomorphology Classification of Shandong Province Based on Digital Elevation Model in the 1 Arc-second Format of Shuttle Radar Topography Mission Data

Science.gov (United States)

Fu, Jundong; Zhang, Guangcheng; Wang, Lei; Xia, Nuan

2018-01-01

Based on gigital elevation model in the 1 arc-second format of shuttle radar topography mission data, using the window analysis and mean change point analysis of geographic information system (GIS) technology, programmed with python modules this, automatically extracted and calculated geomorphic elements of Shandong province. The best access to quantitatively study area relief amplitude of statistical area. According to Chinese landscape classification standard, the landscape type in Shandong province was divided into 8 types: low altitude plain, medium altitude plain, low altitude platform, medium altitude platform, low altitude hills, medium altitude hills, low relief mountain, medium relief mountain and the percentages of Shandong province’s total area are as follows: 12.72%, 0.01%, 36.38%, 0.24%, 17.26%, 15.64%, 11.1%, 6.65%. The results of landforms are basically the same as the overall terrain of Shandong Province, Shandong province’s total area, and the study can quantitatively and scientifically provide reference for the classification of landforms in Shandong province.

The Effect of Landscaping and Building Facades on Perceptual-Behavioral Features of Citizens

Directory of Open Access Journals (Sweden)

Sara Azma

2017-06-01

Full Text Available Objective: Perception could provide the first or the most fundamental layer for recognition and hence, studying it should be prior to any other layer like layers of cultural world and especially, the real world. One of the categories, in which cognition becomes important, is the urban landscape and its designation to improve perceptual perceptions of audiences to enhance items such as sense of belonging and recognition of space and orientation. Therefore, the main purpose of this study is to investigate physical factors affecting urban bodies and its impact on perception and behavior of citizens and considering the gap in this field. Method: The method used in this study is interpretive and in form of qualitative analysis of available references on urban landscape and perception of citizens. The data collected through library research. The procedure is based on classification and content analysis in this study. Results: Landscaping and city walls could lead to emergence of perceptions such as perception of attractiveness and emotions of space, perception of identity and sense of belonging, perception of useful information, perception of hidden order and reagent of life stream, living at the streets, explicit transfer of performance message and perception of urban diversity in citizens. Conclusion: The results obtained from this study could lead to recognizing the relationship between designation and environmental psychology in designing urban landscape and desirable perception of citizens about the environment and the interaction between designation strategies in designing the facade that could finally lead to promotion of quality of the environment and mental comfort and satisfaction of citizens.

Negation handling in sentiment classification using rule-based adapted from Indonesian language syntactic for Indonesian text in Twitter

Science.gov (United States)

Amalia, Rizkiana; Arif Bijaksana, Moch; Darmantoro, Dhinta

2018-03-01

The presence of the word negation is able to change the polarity of the text if it is not handled properly it will affect the performance of the sentiment classification. Negation words in Indonesian are ‘tidak’, ‘bukan’, ‘belum’ and ‘jangan’. Also, there is a conjunction word that able to reverse the actual values, as the word ‘tetapi’, or ‘tapi’. Unigram has shortcomings in dealing with the existence of negation because it treats negation word and the negated words as separate words. A general approach for negation handling in English text gives the tag ‘NEG_’ for following words after negation until the first punctuation. But this may gives the tag to un-negated, and this approach does not handle negation and conjunction in one sentences. The rule-based method to determine what words negated by adapting the rules of Indonesian language syntactic of negation to determine the scope of negation was proposed in this study. With adapting syntactic rules and tagging “NEG_” using SVM classifier with RBF kernel has better performance results than the other experiments. Considering the average F1-score value, the performance of this proposed method can be improved against baseline equal to 1.79% (baseline without negation handling) and 5% (baseline with existing negation handling) for a dataset that all tweets contain negation words. And also for the second dataset that has the various number of negation words in document tweet. It can be improved against baseline at 2.69% (without negation handling) and 3.17% (with existing negation handling).

Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

OpenAIRE

О. О. Dolina; О. М. Smetana

2014-01-01

The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relev...

Classification of high-resolution remote sensing images based on multi-scale superposition

Science.gov (United States)

Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

2017-07-01

Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

Evaluating the landscape impact of renewable energy plants

Science.gov (United States)

Ioannidis, Romanos; Koutsoyiannis, Demetris

2017-04-01

industrialization of landscapes, as the area they require for their constructional and electromechanical works (main body, power station, spillway etc.) is several times smaller than in the other two cases discussed. Moreover, even this small area captured by the dam and is appurtenant structures has potential for architectural and cultural adaptability, which neither wind nor photovoltaic farms have.

Comparison analysis for classification algorithm in data mining and the study of model use

Science.gov (United States)

Chen, Junde; Zhang, Defu

2018-04-01

As a key technique in data mining, classification algorithm was received extensive attention. Through an experiment of classification algorithm in UCI data set, we gave a comparison analysis method for the different algorithms and the statistical test was used here. Than that, an adaptive diagnosis model for preventive electricity stealing and leakage was given as a specific case in the paper.

Deep learning for tumor classification in imaging mass spectrometry.

Science.gov (United States)

Behrmann, Jens; Etmann, Christian; Boskamp, Tobias; Casadonte, Rita; Kriegsmann, Jörg; Maaß, Peter

2018-04-01

Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks. https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS. jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de. Supplementary data are available at Bioinformatics online.

Mapping resource use over a Russian landscape: an integrated look at harvesting of a non-timber forest product in central Kamchatka

International Nuclear Information System (INIS)

Hitztaler, Stephanie K; Bergen, Kathleen M

2013-01-01

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. (letter)

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

Science.gov (United States)

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Relationships between avian richness and landscape structure at multiple scales using multiple landscapes

Science.gov (United States)

Michael S. Mitchell; Scott H. Rutzmoser; T. Bently Wigley; Craig Loehle; John A. Gerwin; Patrick D. Keyser; Richard A. Lancia; Roger W. Perry; Christopher L. Reynolds; Ronald E. Thill; Robert Weih; Don White; Petra Bohall Wood

2006-01-01

Little is known about factors that structure biodiversity on landscape scales, yet current land management protocols, such as forest certification programs, place an increasing emphasis on managing for sustainable biodiversity at landscape scales. We used a replicated landscape study to evaluate relationships between forest structure and avian diversity at both stand...

Landscape Ecology

DEFF Research Database (Denmark)

Christensen, Andreas Aagaard; Brandt, Jesper; Svenningsen, Stig Roar

2017-01-01

, and the ecological significance of the patterns which are generated by such processes. In landscape ecology, perspectives drawn from existing academic disciplines are integrated based on a common, spatially explicit mode of analysis developed from classical holistic geography, emphasizing spatial and landscape...... to translate positivist readings of the environment and hermeneutical perspectives on socioecological interaction into a common framework or terminology....

Landscape stability and water management around the ancient city Jerash, Jordan

Science.gov (United States)

Holdridge, Genevieve; Simpson, Ian; Lichtenberger, Achim; Raja, Rubina; Kristiansen, Søren

2017-04-01

Reduced vulnerability to environmental fluctuations by increasing food and water security increases the resilience of a human society. In the Middle East, there is much archaeological evidence of steady developments and abrupt disasters in cities that have occurred over the millennia, while paleoenvironmental and landscape studies have provided much needed insight into the changes of a citýs surroundings. However, more in-depth urban archaeological studies of soils and sediments on-site, and the interaction of processes on- and off-site are needed to provide new information on human impact and adaptation through time in this region. The present city of Jerash is the location of one of the major Roman urban centers of the Syrian Decapolis. The city was continuously occupied from the Hellenistic period (2nd century BC) to the Umayyad period in the 8th century AD. The city is located along the Wadi Dayr, which feeds into the Zarqa River, and the area is affected by the tectonic activity of the Dead Sea Rift zone. Since the Roman period, various structures were built to manage surface water including rock-cut and plastered channels, water reservoirs and cisterns. Also, during the city's long occupation, slopes were managed by constructing terraces on- and off-site. We have examined the urban and extra-urban fluvial record along the Wadi Dayr in order to better understand urban adaptation and environmental impact of on- and off-site water and land management. By engaging an interdisciplinary approach that incorporates archaeological, paleoclimatic, and geomorphological information, our objective is to discern natural and anthropogenic influences on land and water management. In order to explore human adaptation and impact, we have examined both on- and off-site urban stratigraphy, and are currently analyzing sediments and soils at both landscape and intra-site scales. Profiles in key locations of the wadi offer insight into slope stability (upstream), site land use

Classification of Franchise Networks in the Retail Trade

Directory of Open Access Journals (Sweden)

Grygorenko Tetyana M.

2016-11-01

Full Text Available The article clarifies the definitions of the concepts of «franchise network», «franchise trade network», «franchise retail network», which is substantiated by the lack of a unified approach to interpretation of these concepts. The classification of franchise networks in the retail trade taking into account peculiarities in the operation of this sub-sector of the market economy is developed; classification attributes are identified and types of franchise retail chains are characterized. The proposed classification of franchise retail networks is adapted to the economic situation in Ukraine and specifics of the national franchise relations. It will facilitate a deeper understanding of the essence of the formation and operation of franchise retail chains and also help Ukrainian entrepreneurs to justify choosing the most suitable for them franchising model and allow to establish such a network with regard to various attributes using a complex approach.

Learning as You Journey: Anishinaabe Perception of Social-ecological Environments and Adaptive Learning

Directory of Open Access Journals (Sweden)

Iain Davidson-Hunt

2003-12-01

Full Text Available This paper explores the linkages between social-ecological resilience and adaptive learning. We refer to adaptive learning as a method to capture the two-way relationship between people and their social-ecological environment. In this paper, we focus on traditional ecological knowledge. Research was undertaken with the Anishinaabe people of Iskatewizaagegan No. 39 Independent First Nation, in northwestern Ontario, Canada. The research was carried out over two field seasons, with verification workshops following each field season. The methodology was based on site visits and transects determined by the elders as appropriate to answer a specific question, find specific plants, or locate plant communities. During site visits and transect walks, research themes such as plant nomenclature, plant use, habitat descriptions, biogeophysical landscape vocabulary, and place names were discussed. Working with elders allowed us to record a rich set of vocabulary to describe the spatial characteristics of the biogeophysical landscape. However, elders also directed our attention to places they knew through personal experiences and journeys and remembered from stories and collective history. We documented elders' perceptions of the temporal dynamics of the landscape through discussion of disturbance events and cycles. Again, elders drew our attention to the ways in which time was marked by cultural references to seasons and moons. The social memory of landscape dynamics was documented as a combination of biogeophysical structures and processes, along with the stories by which Iskatewizaagegan people wrote their histories upon the land. Adaptive learning for social-ecological resilience, as suggested by this research, requires maintaining the web of relationships of people and places. Such relationships allow social memory to frame creativity, while allowing knowledge to evolve in the face of change. Social memory does not actually evolve directly out of

Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota

Science.gov (United States)

Corcoran, Jennifer M.; Knight, Joseph F.; Gallant, Alisa L.

2013-01-01

Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.

Cumulative effects of climate and landscape change drive spatial distribution of Rocky Mountain wolverine (Gulo gulo L.).

Science.gov (United States)

Heim, Nicole; Fisher, Jason T; Clevenger, Anthony; Paczkowski, John; Volpe, John

2017-11-01

Contemporary landscapes are subject to a multitude of human-derived stressors. Effects of such stressors are increasingly realized by population declines and large-scale extirpation of taxa worldwide. Most notably, cumulative effects of climate and landscape change can limit species' local adaptation and dispersal capabilities, thereby reducing realized niche space and range extent. Resolving the cumulative effects of multiple stressors on species persistence is a pressing challenge in ecology, especially for declining species. For example, wolverines ( Gulo gulo L.) persist on only 40% of their historic North American range. While climate change has been shown to be a mechanism of range retractions, anthropogenic landscape disturbance has been recently implicated. We hypothesized these two interact to effect declines. We surveyed wolverine occurrence using camera trapping and genetic tagging at 104 sites at the wolverine range edge, spanning a 15,000 km 2 gradient of climate, topographic, anthropogenic, and biotic variables. We used occupancy and generalized linear models to disentangle the factors explaining wolverine distribution. Persistent spring snow pack-expected to decrease with climate change-was a significant predictor, but so was anthropogenic landscape change. Canid mesocarnivores, which we hypothesize are competitors supported by anthropogenic landscape change, had comparatively weaker effect. Wolverine population declines and range shifts likely result from climate change and landscape change operating in tandem. We contend that similar results are likely for many species and that research that simultaneously examines climate change, landscape change, and the biotic landscape is warranted. Ecology research and species conservation plans that address these interactions are more likely to meet their objectives.

Clustering of Groundwater Used in Isfahan Landscape Irrigation and Their Qualititative Changes Over one Decade

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Jahangir Abedi Koupai

2010-06-01

Full Text Available Ten irrigation wells were selected along Chaharbagh Street and the Zayandehrood River bank to investigate and classify the groundwaters used for irrigating Isfahan landscape for their quality. Monthly sampling was performed and the results of the quality tests were used as seasonal averages. Different measurements such as pH, EC, Na+, C1-, HCO3-, Fe+2 were made according to standard methods and the Surfer program was used and the results were represented as isolines. Also seasonal classification of wells was performed based on similarities found among the water quality of the wells using statistical programs. Results revealed the poor quality of water from some of the study wells due to the discharge of urban and industrial wastewaters, chemical manure, etc. Besides, investigation of changes in water quality indicated the declining irrigation water quality and the increasing availability of water for landscape irrigation.

Multi-disciplinary scientists as global change adaptation anchors: Filling the gaps in the Boundary Organization paradigm

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Terando, A. J.; Collazo, J.

2017-12-01

Boundary organizations, entities that facilitate the co-production and translation of scientific research in decision making processes, have been promoted as a means to assist global change adaptation, particularly in the areas of landscape conservation and natural resource management. However, scientists can and often still must perform a similar role and act as anchoring agents within wicked adaptation problems that involve a myriad of actors, values, scientific uncertainties, governance structures, and multidisciplinary research needs. We illustrate one such case study in Puerto Rico's Bosque Modelo (Model Forest) where we discuss an ongoing scientific effort to undertake a multi-objective landscape conservation design project that intersects with the Bosque Modelo geography and goals. Perspectives are provided from two research ecologists, one with a background in terrestrial ecology who has worked at the intersection of science, conservation, and government for over 30 years, and the other with a multi-disciplinary background in earth sciences, climatology, and terrestrial ecology. We frame our discussion around the learning process that accompanies the development of global change scenarios that are both useful and useable for a wide spectrum of scientists, and the likelihood that scientifically informed adaptive management actions will ultimately be implemented in this complex and changing landscape.

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

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Qiyang Xiao

2016-12-01

Full Text Available 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.

Ecological mechanisms underpinning climate adaptation services.

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Lavorel, Sandra; Colloff, Matthew J; McIntyre, Sue; Doherty, Michael D; Murphy, Helen T; Metcalfe, Daniel J; Dunlop, Michael; Williams, Richard J; Wise, Russell M; Williams, Kristen J

2015-01-01

Ecosystem services are typically valued for their immediate material or cultural benefits to human wellbeing, supported by regulating and supporting services. Under climate change, with more frequent stresses and novel shocks, 'climate adaptation services', are defined as the benefits to people from increased social ability to respond to change, provided by the capability of ecosystems to moderate and adapt to climate change and variability. They broaden the ecosystem services framework to assist decision makers in planning for an uncertain future with new choices and options. We present a generic framework for operationalising the adaptation services concept. Four steps guide the identification of intrinsic ecological mechanisms that facilitate the maintenance and emergence of ecosystem services during periods of change, and so materialise as adaptation services. We applied this framework for four contrasted Australian ecosystems. Comparative analyses enabled by the operational framework suggest that adaptation services that emerge during trajectories of ecological change are supported by common mechanisms: vegetation structural diversity, the role of keystone species or functional groups, response diversity and landscape connectivity, which underpin the persistence of function and the reassembly of ecological communities under severe climate change and variability. Such understanding should guide ecosystem management towards adaptation planning. © 2014 John Wiley & Sons Ltd.

A simple approach for a spatial terrestrial exposure assessment of the insecticide fenoxycarb, based on a high-resolution landscape analysis.

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Thomas, Kai; Resseler, Herbert; Spatz, Robert; Hendley, Paul; Sweeney, Paul; Urban, Martin; Kubiak, Roland

2016-11-01

The objective was to refine the standard regulatory exposure scenario used in plant protection product authorisations by developing a more realistic landscape-related GIS-based exposure assessment for terrestrial non-target arthropods. We quantified the proportion of adjacent off-target area in agricultural landscapes potentially exposed to insecticide drift from applications of the active substance fenoxycarb. High-resolution imagery, landscape classification and subsequent stepwise analysis of a whole landscape using drift and interception functions were applied to selected areas in representative fruit-producing regions in Germany. Even under worst-case assumptions regarding treated area, use rate and drift, less than 12% of the non-agricultural habitat area would potentially be exposed to fenoxycarb drift above regulatory acceptable concentrations. Additionally, if the filtering effect of tall vegetation were taken into account, this number would decrease to 6.6%. Further refinements to landscape elements and application conditions indicate that less than 5% of the habitat area might be exposed above regulatory acceptable concentrations, meaning that 95% of the non-agricultural habitat area will be unimpacted (i.e. no unacceptable effects) and can serve as refuge for recolonisation. Approaches and tools are proposed for standardisable and transparent refinements in regulatory risk assessments on the landscape level. © 2016 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2016 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A Tale of Two Regions: Landscape Ecological Planning for Shale Gas Energy Futures

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Murtha, T., Jr.; Schroth, O.; Orland, B.; Goldberg, L.; Mazurczyk, T.

2015-12-01

As we increasingly embrace deep shale gas deposits to meet global energy demands new and dispersed local and regional policy and planning challenges emerge. Even in regions with long histories of energy extraction, such as coal, shale gas and the infrastructure needed to produce the gas and transport it to market offers uniquely complex transformations in land use and landcover not previously experienced. These transformations are fast paced, dispersed and can overwhelm local and regional planning and regulatory processes. Coupled to these transformations is a structural confounding factor. While extraction and testing are carried out locally, regulation and decision-making is multilayered, often influenced by national and international factors. Using a geodesign framework, this paper applies a set of geospatial landscape ecological planning tools in two shale gas settings. First, we describe and detail a series of ongoing studies and tools that we have developed for communities in the Marcellus Shale region of the eastern United States, specifically the northern tier of Pennsylvania. Second, we apply a subset of these tools to potential gas development areas of the Fylde region in Lancashire, United Kingdom. For the past five years we have tested, applied and refined a set of place based and data driven geospatial models for forecasting, envisioning, analyzing and evaluating shale gas activities in northern Pennsylvania. These models are continuously compared to important landscape ecological planning challenges and priorities in the region, e.g. visual and cultural resource preservation. Adapting and applying these tools to a different landscape allow us to not only isolate and define important regulatory and policy exigencies in each specific setting, but also to develop and refine these models for broader application. As we continue to explore increasingly complex energy solutions globally, we need an equally complex comparative set of landscape ecological

Impact of landscape characteristics on the stream carbon and nitrogen export: example of a small agricultural catchment in Denmark

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Wohlfart, T.; Exbrayat, J.F.; Schelde, Kirsten

2012-01-01

Agriculture plays an important role on the environment, notably the quality of water draining cultivated soils. Understanding the relationship between landscape characteristics and stream quality is crucial to sustain a good quality of water and to develop adapted policies. Therefore, this study...... point between the chemical data and landscape characteristics (e.g. topography, land-use and soil type distributions) of the corresponding contributing area. Results show that, in spite of an overall little share, the influence of organic soil types seems to impact N losses to streams stronger than...... local land use by farming....

Modeling brook trout presence and absence from landscape variables using four different analytical methods

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Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Landscape Ecology and problems of European cultural landscapes

DEFF Research Database (Denmark)

Brandt, Jesper

2011-01-01

by practical problems of European cultural – especial agricultural – landscapes since the rise of the environmental movement. Central themes have been the consequences of technological and structural changes within European agriculture for the landscape and the development of habitats and dispersal...... Problemstellungen basieren auf multifunktionalen Nutzungskonzepten ruraler Landschaften, besonders im Hinblick auf Suburbanisierungsprozesse. Eine Anzahl untereinander vergleichbarer Projekte, mit parallelen bis ähnlichen Ausprägungen innerhalb Dänemarks und weiteerer europäischer Länder, werden exemplarisch...

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

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Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

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Qi Huang

2017-06-01

Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

Landscape Builder: Software for the creation of initial landscapes for LANDIS from FIA data

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