Landscape connectivity is important for energy and material flow in ecosystems as well as for the survival of species. The landscape structure influences and reflects the degree of landscape connectivity. In order to ...Landscape connectivity is important for energy and material flow in ecosystems as well as for the survival of species. The landscape structure influences and reflects the degree of landscape connectivity. In order to study the coupling relationship between landscape structure and connectivity and reveal the succession relationship between its structure and connectivity in the typical karst plateau area. The study analyzed the typical area of Houzhai River in Puding County, Anshun City, Guizhou Province, according to the landscape pattern index and probability landscape connectivity index. The results show:(1) The landscape structure of the study area A is mainly characterized by large patches and uniform distribution. The main land is woodland and cultivated land, and the overall landscape is low fragmentation.(2) The landscape structure of the study area B is mainly characterized by the clustering of a certain type of land cover and the uneven distribution of the patches, for example, cultivated land. Other types of patches are scatteredly distributed, and the overall landscape is highly fragmented.(3) The study area A, B in 100, 500, 1000, 2000, 3000, 5 distance thresholds of landscape connectivity were 1.55, 1.99, 2.26, 2.49, 2.58 and 0.02, 0.10, 0.15, 0.19, 0.20, respectively. The average landscape connectivity is 2. 18 and 0. 13, respectively. Study Area A has a higher degree of landscape connectivity than B. Landscape pattern indicators can represent the landscape structure and probability landscape connectivity index calculates the landscape connectivity in the study area. The results of the study can provide a basis for ecological restoration of plateau karst regions and well-oriented rural development planning.展开更多
Quantification of complicated surface morphology of soil crack is a prerequisite and key to soil crack study. This paper takes soil crack quads in Yuanmou arid-hot valley region as examples, selecting several morpholo...Quantification of complicated surface morphology of soil crack is a prerequisite and key to soil crack study. This paper takes soil crack quads in Yuanmou arid-hot valley region as examples, selecting several morphological indicators, and analyzes the soil crack＇s morphological features under various development degrees. By statistic analysis, three quantitative indicators for surface morphology are selected, namely soil crack area density, area weighted mean fractal dimension and connectivity index R, which can not only express the development intensity of soil cracks, but also effectively describe its morphological complexity and connectivity. The research results set a good base for the establishment of soil crack assessment system in Yuanmou arid-hot valley region.展开更多
This paper attempts to analyze the functions of hypo-cities in the context of regional economic integration and further studies how hypo-cities with different characteristics exploit their advantages to the full,putti...This paper attempts to analyze the functions of hypo-cities in the context of regional economic integration and further studies how hypo-cities with different characteristics exploit their advantages to the full,putting forward the development strategy of hypo-cities in the transportation integration.展开更多
Text extraction is the key step in the character recognition;its accuracy highly relies on the location of the text region. In this paper, we propose a new method which can find the text location automatically to solv...Text extraction is the key step in the character recognition;its accuracy highly relies on the location of the text region. In this paper, we propose a new method which can find the text location automatically to solve some regional problems such as incomplete, false position or orientation deviation occurred in the low-contrast image text extraction. Firstly, we make some pre-processing for the original image, including color space transform, contrast-limited adaptive histogram equalization, Sobel edge detector, morphological method and eight neighborhood processing method (ENPM) etc., to provide some results to compare the different methods. Secondly, we use the connected component analysis (CCA) method to get several connected parts and non-connected parts, then use the morphology method and CCA again for the non-connected part to erode some noises, obtain another connected and non-connected parts. Thirdly, we compute the edge feature for all connected areas, combine Support Vector Machine (SVM) to classify the real text region, obtain the text location coordinates. Finally, we use the text region coordinate to extract the block including the text, then binarize, cluster and recognize all text information. At last, we calculate the precision rate and recall rate to evaluate the method for more than 200 images. The experiments show that the method we proposed is robust for low-contrast text images with the variations in font size and font color, different language, gloomy environment, etc.展开更多
An improvement of tolerance relation is proposed in regard to rough set model based on connection degree by which reflexivity of relation can be assured without loss of information. Then, a method to determine optimal...An improvement of tolerance relation is proposed in regard to rough set model based on connection degree by which reflexivity of relation can be assured without loss of information. Then, a method to determine optimal identity degree based on relative positive region is proposed so that the identity degree can be computed in an objective method without any preliminary or additional information about data, which is consistent with the notion of objectivity in rough set theory and data mining theory. Subsequently, an algorithm is proposed, and in two examples, the global optimum identity degree is found out. Finally, in regard to optimum connection degree, the method of rules extraction for connection degree rough set model based on generalization function is presented by which the rules extracted from a decision table are enumerated.展开更多
文摘Landscape connectivity is important for energy and material flow in ecosystems as well as for the survival of species. The landscape structure influences and reflects the degree of landscape connectivity. In order to study the coupling relationship between landscape structure and connectivity and reveal the succession relationship between its structure and connectivity in the typical karst plateau area. The study analyzed the typical area of Houzhai River in Puding County, Anshun City, Guizhou Province, according to the landscape pattern index and probability landscape connectivity index. The results show:(1) The landscape structure of the study area A is mainly characterized by large patches and uniform distribution. The main land is woodland and cultivated land, and the overall landscape is low fragmentation.(2) The landscape structure of the study area B is mainly characterized by the clustering of a certain type of land cover and the uneven distribution of the patches, for example, cultivated land. Other types of patches are scatteredly distributed, and the overall landscape is highly fragmented.(3) The study area A, B in 100, 500, 1000, 2000, 3000, 5 distance thresholds of landscape connectivity were 1.55, 1.99, 2.26, 2.49, 2.58 and 0.02, 0.10, 0.15, 0.19, 0.20, respectively. The average landscape connectivity is 2. 18 and 0. 13, respectively. Study Area A has a higher degree of landscape connectivity than B. Landscape pattern indicators can represent the landscape structure and probability landscape connectivity index calculates the landscape connectivity in the study area. The results of the study can provide a basis for ecological restoration of plateau karst regions and well-oriented rural development planning.
基金the National Natural Science Foundation of China (30470297)the National Key Technologies Research and Development Program in the Eleventh Five-Year Plan of China (2006BAC01A11)the Youth Foundation of Institute of Mountain Hazards and Environment of Chinese Academy of Sciences
文摘Quantification of complicated surface morphology of soil crack is a prerequisite and key to soil crack study. This paper takes soil crack quads in Yuanmou arid-hot valley region as examples, selecting several morphological indicators, and analyzes the soil crack＇s morphological features under various development degrees. By statistic analysis, three quantitative indicators for surface morphology are selected, namely soil crack area density, area weighted mean fractal dimension and connectivity index R, which can not only express the development intensity of soil cracks, but also effectively describe its morphological complexity and connectivity. The research results set a good base for the establishment of soil crack assessment system in Yuanmou arid-hot valley region.
文摘This paper attempts to analyze the functions of hypo-cities in the context of regional economic integration and further studies how hypo-cities with different characteristics exploit their advantages to the full,putting forward the development strategy of hypo-cities in the transportation integration.
文摘Text extraction is the key step in the character recognition;its accuracy highly relies on the location of the text region. In this paper, we propose a new method which can find the text location automatically to solve some regional problems such as incomplete, false position or orientation deviation occurred in the low-contrast image text extraction. Firstly, we make some pre-processing for the original image, including color space transform, contrast-limited adaptive histogram equalization, Sobel edge detector, morphological method and eight neighborhood processing method (ENPM) etc., to provide some results to compare the different methods. Secondly, we use the connected component analysis (CCA) method to get several connected parts and non-connected parts, then use the morphology method and CCA again for the non-connected part to erode some noises, obtain another connected and non-connected parts. Thirdly, we compute the edge feature for all connected areas, combine Support Vector Machine (SVM) to classify the real text region, obtain the text location coordinates. Finally, we use the text region coordinate to extract the block including the text, then binarize, cluster and recognize all text information. At last, we calculate the precision rate and recall rate to evaluate the method for more than 200 images. The experiments show that the method we proposed is robust for low-contrast text images with the variations in font size and font color, different language, gloomy environment, etc.
基金supported by the National Natural Science Foundation of China (70571032)
文摘An improvement of tolerance relation is proposed in regard to rough set model based on connection degree by which reflexivity of relation can be assured without loss of information. Then, a method to determine optimal identity degree based on relative positive region is proposed so that the identity degree can be computed in an objective method without any preliminary or additional information about data, which is consistent with the notion of objectivity in rough set theory and data mining theory. Subsequently, an algorithm is proposed, and in two examples, the global optimum identity degree is found out. Finally, in regard to optimum connection degree, the method of rules extraction for connection degree rough set model based on generalization function is presented by which the rules extracted from a decision table are enumerated.
