Morphing of Building Footprints Using a Turning Angle Function

We study the problem of morphing two polygons of building footprints at two different scales. This problem frequently occurs during the continuous zooming of interactive maps. The ground plan of a building footprint on a map has orthogonal characteristics, but traditional morphing methods cannot preserve these geographic characteristics at intermediate scales. We attempt to address this issue by presenting a turning angle function-based morphing model (TAFBM) that can generate polygons at an intermediate scale with an identical turning angle for each side. Thus, the orthogonal characteristics can be preserved during the entire interpolation. A case study demonstrates that the model yields good results when applied to data from a building map at various scales. During the continuous generalization, the orthogonal characteristics and their relationships with the spatial direction and topology are well preserve

Fine Mapping of the Bsr1 Barley Stripe Mosaic Virus Resistance Gene in the Model Grass Brachypodium distachyon

The ND18 strain of Barley stripe mosaic virus (BSMV) infects several lines of Brachypodium distachyon, a recently developed model system for genomics research in cereals. Among the inbred lines tested, Bd3-1 is highly resistant at 20 to 25°C, whereas Bd21 is susceptible and infection results in an intense mosaic phenotype accompanied by high levels of replicating virus. We generated an F6∶7 recombinant inbred line (RIL) population from a cross between Bd3-1 and Bd21 and used the RILs, and an F2 population of a second Bd21 × Bd3-1 cross to evaluate the inheritance of resistance. The results indicate that resistance segregates as expected for a single dominant gene, which we have designated Barley stripe mosaic virus resistance 1 (Bsr1). We constructed a genetic linkage map of the RIL population using SNP markers to map this gene to within 705 Kb of the distal end of the top of chromosome 3. Additional CAPS and Indel markers were used to fine map Bsr1 to a 23 Kb interval containing five putative genes. Our study demonstrates the power of using RILs to rapidly map the genetic determinants of BSMV resistance in Brachypodium. Moreover, the RILs and their associated genetic map, when combined with the complete genomic sequence of Brachypodium, provide new resources for genetic analyses of many other traits

Gene-gene Interaction Analyses for Atrial Fibrillation

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in a

Steering Angle Function Algorithm of Morphing of Residential Area

A residential area feature morphing method based on steering angle function is presented. To residential area with the same representation under two different scales,transforming the representation of the residential area polygon from vector coordinates to steering angle function,then using the steering angle function to match,and finding out the similarity and the differences between the residential areas under different scale to get the steering angle function of the the residential areas under any middle scale,the final,transforming the middle scale steering angle function to vector coordinates form,and get the middle shape interpolation of the the residential area polygon.Experimental results show:the residential area morphing method by using steering angle function presented can realize the continuous multi-scale representation under the premise of keeping in shape for the residential area with the rectangular boundary features

An Ontology-Based Framework for Complex Urban Object Recognition through Integrating Visual Features and Interpretable Semantics

Although previous works have proposed sophisticatedly probabilistic models that has strong capability of extracting features from remote sensing data (e.g., convolutional neural networks, CNN), the efforts that focus on exploring the human’s semantics on the object to be recognized are required more explorations. Moreover, interpretability of feature extraction becomes a major disadvantage of the state-of-the-art CNN. Especially for the complex urban objects, which varies in geometrical shapes, functional structures, environmental contexts, etc, due to the heterogeneity between low-level data features and high-level semantics, the features derived from remote sensing data alone are limited to facilitate an accurate recognition. In this paper, we present an ontology-based methodology framework for enabling object recognition through rules extracted from the high-level semantics, rather than unexplainable features extracted from a CNN. Firstly, we semantically organize the descriptions and definitions of the object as semantics (RDF-triple rules) through our developed domain ontology. Secondly, we exploit semantic web rule language to propose an encoder model for decomposing the RDF-triple rules based on a multilayer strategy. Then, we map the low-level data features, which are defined from optical satellite image and LiDAR height, to the decomposed parts of RDF-triple rules. Eventually, we apply a probabilistic belief network (PBN) to probabilistically represent the relationships between low-level data features and high-level semantics, as well as a modified TanH function is used to optimize the recognition result. The experimental results on lacking of the training process based on data samples show that our proposed approach can reach an accurate recognition with high-level semantics. This work is conducive to the development of complex urban object recognition toward the fields including multilayer learning algorithms and knowledge graph-based relational reinforcement learning

Spatio-Temporal Processes and Characteristics of Vegetation Recovery in the Earthquake Area: A Case Study of Wenchuan, China

The quantitative and qualitative assessment of post-disaster vegetation damage and recovery in the core area of the Wenchuan earthquake is of great significance for the restoration and reconstruction of natural ecosystems and the construction of human settlements in China. This study used time series analysis to determine the time of MODIS data and used the data to study the vegetation damage and restoration in the core area of the Wenchuan earthquake. The determined MODIS images were used to quantitatively analyze a series of vegetation damage changes and the vegetation recovery rate in the core area of the Wenchuan earthquake before and after the earthquake. By applying the topographic factors, we analyzed the spatial and temporal characteristics of the dynamic changes of vegetation damage and the recovery rate in the disaster area. The results show that the study area’s vegetation damage was correlated to topographic factors and distance from towns. Besides, the overall vegetation restoration after the disaster was relatively optimistic. In some areas, the vegetation restoration level even exceeded the vegetation coverage level before the disaster. The recovery study of MODIS-NDVI showed a specific lag delay effect on the image of vegetation cover. The vegetation damage and the recovery rate of vegetation cover were significantly correlated with the distance from towns and the topographic factor. Overall, the results contribute to the theoretical support for the damage and recovery of vegetation in the core area affected by the earthquake

Classification Method and Determination of Mountainous Area Types at Township Scales: A Case Study of Yuxi City, Yunnan Province

The high-resolution regional division of mountainous area types has important scientific significance for promoting precise management of land space and regional sustainable development. At present, the classification method of mountainous area types is mainly at the county level and above, while classifications for towns and villages are nearly nonexistent, which poses a technical challenge for rural revitalization and the construction of ecological civilization in mountainous areas. We used Yuxi city, Yunnan Province, as the target area of this research, which was based on GIS technology and Digital Elevation Model (DEM) data and socioeconomic environmental monitoring data. The most appropriate statistical unit (e.g., 2.8224 km2) for topographic relief was defined, and the study area was divided into six mountain types: flatlands, hills, low mountains, medium-low mountains, midmountains, and subhigh mountains. Based on the township scale, an index system and classification method dominated by the plain comprehensive index were established to carry out mountain area classifications at township scales. The 75 towns of Yuxi city can be classified into 27 plain towns, 23 mountain-plain towns, and 25 mountain towns from an empirical application perspective, which can provide strong data support and a reference basis for studying the evolution characteristics of land use in different geographical spaces and their interrelationships as well as differentiated land space planning and governance

Urban Comprehensive Carrying Capacity and Urbanization in Northeast China

The scientific evaluation and identification of the relationship between urban comprehensive carrying capacity and urbanization in Northeast China, a famous old industrial base, is an important basis for realizing the overall revitalization of the region. Using a panel data set of 34 prefecture-level cities in Northeast China from 2003 to 2019, this study constructs an ordinary panel data model to identify the relationship between urban comprehensive carrying capacity and urbanization. The results show that urbanization has significantly positive effects on urban comprehensive carrying capacity, and there is a significant inverted U-shaped curve relationship between urban comprehensive carrying capacity and comprehensive urbanization in Northeast China, especially in the shrinking cites. In addition, the economic urbanization variables of the fixed-asset investment, the total retail sales of social consumer goods, and the social urbanization variable of internet users play significantly important roles in forming of the inverted U-shaped curve relationship with the urban comprehensive carrying capacity of the shrinking cities in Northeast China. Hence, innovation-driven economic regrowth, promoting equalization of basic public services, alleviating talent outflow, and strengthening the leading roles of the core cities are effective measures for improving urban comprehensive carrying capacity and urbanization quality in Northeast China

Identification of Urban Functional Area by Using Multisource Geographic Data: A Case Study of Zhengzhou, China

The rational allocation of functional areas is the foundation for addressing the sustainable development of cities. Efficient and accurate identification methods of urban functional areas are of great significance to the adjustment and testing of urban planning and industrial layout optimization. Firstly, by employing multisource geographic data, an identification method of urban functional areas was developed. A quantitative measurement approach of the urban functional area was then established considering the comprehensive effects of human-land, space-time, and thematic information to present the covering area of ground objects, public awareness, and empirical research. Finally, the Zhengzhou city, which locates in Henan province of central China, was used to test the method. The results show that the developed method is efficient, accurate, and universal and can identify urban functional areas quickly and accurately. We found that the overall distribution of Zhengzhou’s functional areas presents a spatial pattern of single and multimixed coordinated development. The city’s commercial functional areas and commercial-based mixed functional areas are located in the city’s central area. The green square’s function area occupies relatively low and is mainly distributed in the city’s fringe