Edge Density Index Research Articles

A Novel Approach to Evaluate the Wear Behavior of CuO Doped Sintered Alumina Ceramics Using Image Processing Models

The present research describes the post wear SEM images of nano-CuO doped alumina ceramics in the light of three different image processing algorithms, viz. entropy analysis, Sobel edge detection techniques and entropy filtered image histogram analysis. The 2 wt% CuO doped sintered alumina has shown the best performance towards wearing due to maximum bulk density, hardness and fracture toughness. These materialistic properties are fitted to correlate with the lowest value of entropy and edge density index at the level of 2 wt% doping. The entropy filtered image histogram of 2 wt% doping is the closest to the Gaussian Bell shape distribution with the lowest skewness factor. These three-image computed methods validate their suitability in developing a real-life implementation for a possible wear resistance estimator.

A novel complex network community clustering method for fault diagnosis

The complex network, as a method for the analysis of nonlinear and non-stationary signals, overcomes the shortcomings of traditional time-frequency analysis methods and proves its effectiveness in mechanical fault diagnosis. Community clustering, a type of complex network, has made great progress in recent years. However, the existing community clustering algorithms have disadvantages in that they lack significant global extreme value and huge search spaces. Therefore, a Fast Newman algorithm based on reliability judgment is proposed. Starting from the community structure characteristics of the complex network, with the fault sample as a network node, the relationship between the samples as a connected edge and a complex network model of fault data is established. Clusters in troubleshooting are transformed into community structure discovery in the network. Firstly, the initial division of the community is obtained by measuring the distance between the samples. Then, the modularity index of the network is used as a standard function of the community division, and the bottom-up community merger is performed. The local edge density index is used for reliability determination before each combination to achieve global optimization, and the network block structure is the most obvious. Finally, with all the data merged into one community, the optimal division of the community structure is obtained, while accurate community clustering and fault diagnosis is realized. The benchmark graphs for testing community detection (Lancichinetti–Fortunato–Radicchi benchmark standard test network, LFR) and different fault data of rolling bearings under multiple operating conditions are applied to verify the effectiveness of this method; the results prove that the modified Fast Newman algorithm has better clustering effects and a higher accuracy rate than the original algorithm. Compared with K-means clustering and fuzzy clustering, the modified Fast Newman algorithm achieves higher performance in fault diagnosis of rolling bearings under multiple operating conditions.

Effects of straw returning to movement characteristics of soil preferential flow in sugarcane fields

The measures of returning straw to the field can change soil environment in the field and affect crop growth. In order to explore the impacts of different straw returning measures on the preferential flow in the field, we investigated the movement characteristics of preferential flow in sugarcane fields under different straw returning measures [straw mulching (CM), straw burning mulching (BM), and non-straw mulching (CK)] in Guangxi by combining image analysis techniques with ecological landscape pattern analysis methods. The results showed that under the same external water supply environment, soil staining morphology of non-straw mulching sugarcane fields differentiated into finger-like and clump-like. Both straw mulching and straw burning mulching were mainly differentiated into clump-like. The mean total staining area ratio was significantly higher than that of non-straw mulching (26.0%). The ratio of surface staining area decreased rapidly under non-straw mulching. The water movement range decreased rapidly under straw mulching and straw burning mulching in the depth of 15-30 cm. The change rate of straw mulching staining area ratio was the lowest in the deep soil. The shape index of non-straw mulching was 15.54. The water flow movement was more concentrated. The average sub-circular index of straw mulching and straw burning mulching was 0.67 in the sugarcane field, with a higher degree of preferential flow bending, an average proximity index of 0.87, and better water flow connectivity. The average substrate flow depth (3.52 cm) and edge density index (11.51) were the smallest under non-straw mulching, but the priority flow ratio was the largest (73.2%), and the spatial development degree of preferential flow was the highest. The straw returning measures reduced the preferential flow in the sugarcane fields, with positive effects on water conservation.

Innovative Approach to Evaluate the Wearing of Nano-TiO2-Doped Alumina Ceramics in the Light of Image Modeling

Abstract The present research is emphasized on the microscopic observation of post-wear surface of nano-TiO2-doped alumina ceramics to access wearing by promising image processing algorithms, namely, entropy analysis, Sobel edge detection technique, and entropy filtered image histogram analysis in relation to the extent of doping. The experimental results of specific wear-rate showed an indicator with the extent of microfracturing of grains, plowing of materials and debris formation on the wear track after a long wear cycle in terms of entropy level, edge density index, and entropy filtered image, and the nature of histogram at different doping levels. The lowest value of entropy level and edge density index is shown at the level of 1 wt%. TiO2-doped alumina ceramics due to the presence of low number of granularity and microfracture grains on the wear track cause the lowering of specific wear-rate. The histogram of entropy filtered image for 1 wt% doping is more uniformly distributed with the highest frequency and lowest skewness factor over a wide range of intensity values.

Mapping temporal changes in landscape spatial heterogeneity using the contrast weighted edge density index

The aim of this study is to map and analyze the temporal changes in the landscape structural heterogeneity over the past 40 years in a brutian pine (Pinus brutia Ten.) dominated forest area in the Mediterranean region of Turkey. The change detection analysis was done based on two forest stand maps belonging to 1966 and 2006 years. We used the Contrast Weighted Edge Density Index (CWEDI) for quantifying landscape structural heterogeneity. The study area was converted to 500 x 500 m grid cells and then a CWEDI value was calculated for each cell. The temporal differences were determined by subtracting the cell values in the heterogeneity map of 2006 year from the corresponding cell values in the map of 1966 year. In the change map, we perceived that the changes in 24% of the area (2364.93 ha) resulted from the management activities. The changes in the rest of study area (7471.75 ha) might occur due to other factors except management activities such as the natural growth in the stands or the photo-interpretation differences between the two measurement times. The study results show that the even-aged management has promoted the artificial edges between brutian pine stands with different ages while it has reduced the natural edges. Although the patchiness generated by the wood-oriented management may positively affect edge-dwelling species, it may have negatively influences on edge-sensitive species. As a result, a biodiversity-friendly forest management strategy should be developed to maintain a good balance between wood production and non-wood forest values in the brutian forests.

Wavelet-Based Correlation Identification of Scales and Locations between Landscape Patterns and Topography in Urban-Rural Profiles: Case of the Jilin City, China

Landscapes display overlapping sets of correlations in different regions at different spatial scales, and these correlations can be delineated by pattern analysis. This study identified the correlations between landscape pattern and topography at various scales and locations in urban-rural profiles from Jilin City, China, using Pearson correlation analysis and wavelet method. Two profiles, 30 km (A) and 35 km (B) in length with 0.1-km sampling intervals, were selected. The results indicated that profile A was more sensitive to the characterization of the land use pattern as influenced by topography due to its more varied terrain, and three scales (small, medium, and large) could be defined based on the variation in the standard deviation of the wavelet coherency in profile A. Correlations between landscape metrics and elevation were similar at large scales (over 8 km), while complex correlations were discovered at other scale intervals. The medium scale of cohesion and Shannon’s diversity index was 1–8 km, while those of perimeter-area fractal dimension and edge density index were 1.5–8 km and 2–8 km, respectively. At small scales, the correlations were weak as a whole and scattered due to the micro-topography and landform elements, such as valleys and hillsides. At medium scales, the correlations were most affected by local topography, and the land use pattern was significantly correlated with topography at several locations. At large spatial scales, significant correlation existed throughout the study area due to alternating mountains and plains. In general, the strength of correlation between landscape metrics and topography increased gradually with increasing spatial scale, although this tendency had some fluctuations in several locations. Despite a complex calculating process and ecological interpretation, the wavelet method is still an effective tool to identify multi-scale characteristics in landscape ecology.

内蒙古高格斯台罕乌拉自然保护区土地覆盖与景观格局变化分析

土地覆盖变化和景观格局变化是研究生态环境变化及野生动物生境格局变化的重要基础。本研究基于内蒙古高格斯台罕乌拉国家级自然保护区1995、2004和2014年7月份3期landsat TM系列数据，运用RS、GIS技术及景观生态学的方法，系统分析了该区1995~2014年土地覆盖与景观格局变化，定量分析了土地覆盖类型变化度、斑块面积指数、斑块形状指数、边缘密度指数以及多样性指数等指标。研究结果表明：土地覆盖类型主要为草地、林地和灌丛半灌丛，约占保护区总面积的80%~90%；其中1995~2014年草地面积减少245.74 km2，林地增加99.73 km2，灌丛半灌木丛减少4.38 km2；从景观格局来看，1995~2014年间，斑块数量、斑块密度、平均形状指数均有较大波动，均为先增加后减少；而聚集度先变小后又增大；Shannon’s多样性指数逐渐递增，最大斑块指数逐渐减小。说明1995~2004年，景观趋于丰富和复杂化，2004年以后，破碎化程度减小并趋于稳定。该研究结果表明随保护区级别晋升，管护力度加大，保护区环境得到改善，但仍然面临土地退化的严重挑战。 Land coverage and landscape pattern changes are the important basis of the study in the change of ecological environment and wildlife habitat pattern. In our study, we got the three phases dataset of lands at TM at summer in July 1995, 2004 and 2014 in Gaogesitai-Hanwula national nature reserve, Inner Mongolia, and used techniques of remote sensing (RS), geographic information systems (GIS) and landscape pattern analysis method to systematically analyze the land coverage and landscape pattern change from 1995 to 2014, and quantificationally analyze land cover types change degrees, patch area index, patch shape index, edge density index and diversity index. Our results showed the grassland, woodland, brush and half shrubs were the main land coverage type. They occupied 80% - 90% of the total area. From 1995 to 2014, grassland decreased by 245.74 km2, forest land increased by 99.73 km2 and brush and half shrubs decreased by 4.38 km2. From 1995 to 2014 by the landscape pattern, patch number, patch density and mean shape index showed great fluctuations (increased firstly and then decreased quickly); the degree of aggregation firstly decreased and then increased; Shannon’s diversity indices gradually increased; and the largest patch index gradually decreased. It showed the landscape tended to be more abundant and complex from 1995 to 2004, and the degree of fragmentation was decreasing and tending to be stable. Our results also showed as the promotion of the level and the improvement of protection for the nature reserve, the environment of nature reserve was improved. However, it still faced the enormous challenge due to the land degradation.

Impacts of edge density of field patches on plant species richness and community turnover among margin habitats in agricultural landscapes

In intensive agricultural environments, arable field margins are important habitats as reservoirs of various beneficial wild species. Many studies of species diversity in field margins have focused on the local habitat level. However, relationships between the network of the margin habitats and species diversity are less studied.Edge density index of field patches is a class-level landscape metric used as one measure of habitat network. This study focused on edge density index and its impacts on plant species richness and community turnover among the margins in agricultural landscapes. We examined how effectively the index of edge density can be used as a class-level indicator for species diversity in margins. This study introduces a method for indicating plant species diversity of the margin habitats by using an easily measured spatial indicator without comprehensive analysis of land use/land cover.A total of 29 landscape-square pairs, each consisting of two 25ha squares, were sampled across southern Finland. Vascular plant species were sampled in each square. In GIS, field patch edges were divided into two types: those within crop fields, referred to as within-field edges, and those between crop fields and non-crop lands, referred to as non-crop field edges.By comparing the roles of three landscape groups (the two different edge types as well as all edges grouped together) in explaining plant species richness (at alpha and gamma level) and community turnover (at beta level) in the sampled landscape squares, we found that density index of non-crop field edges surrounded by contrast land use is an effective indicator of species diversity at beta and gamma level. This study suggested that field margins surrounded by contrast land use shall be considered as a priority landscape element in agricultural edge network design, whereas simply using the density of all field edges to indicate species diversity without separating the different effects of various edge types shall not be recommended.