Acta Geodaetica et Cartographica Sinica

The spectral analysis and application of low-degree modified spheroidal Hotine kernel

MA Jian, WEI Ziqing, REN Hongfei

2019, 48(5): 537-546. doi:10.11947/j.AGCS.2019.20170613

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The traditional spheroidal kernel results in the spectrum leakage, and the utilization rate of the removed degrees of the measured data is low. Hence, a kind of spheroidal kernel whose high and low degrees are both modified is introduced in this research, which is exampled by the Hotine kernel. In addition, the low-degree modified spheroidal kernel is proposed. Either cosine or linear modification factors can be utilized. The modified kernel functions can effectively control the spectrum leakage compared with the traditional spheroidal kernel. Furthermore, the modified kernel augments the contribution rate of the measured data to the height anomaly in the modified frequency domain. The experimental results show that the accuracies of the quasi-geoids using the cosine and linear low-degree modified kernels are higher than the traditional spheroidal kernel, and differ little from the accuracies of the quasi-geoids using the kernel whose high and low degrees are both modified when the low-degree modification widths of these two kinds of kernels are the same. Since the computational efficiency of the low-degree modified kernel is improved obviously, the low-degree modified kernel behaves better in constructing the (quasi-) geoid based on Stokes-Helmert or Hotine-Helmert boundary value theory.

Detecting droughts in Southwest China from GPS vertical position displacements

YAO Chaolong, LUO Zhicai, HU Yueming, WANG Changwei, ZHANG Rui, LI Jinming

2019, 48(5): 547-554. doi:10.11947/j.AGCS.2019.20180308

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The solid Earth responds elastically to terrestrial water storage (TWS) changes. Here global positioning system(GPS)vertical position data at 31 stations from crustal movement observation network of China (CMONOC)from August 2010 to December 2016 are used to detect droughts in Southwest China. Monthly GPS vertical position displacements respond negatively to precipitation changes and TWS changes observed by gravity recovery and climate experiment(GRACE) as well as river water level variations. GPS vertical position anomalies (the nonseasonal term) are well correlated negatively (correlations of about -0.70) with the commonly used meteorological composite index (CI) in China and the GRACE drought severity index (GRACE-DSI), but less correlated with the standardized precipitation evapotranspiration index (SPEI). Compared to CI, GPS vertical position anomalies have the advantage in detecting droughts caused by abrupt precipitation deficits in a short time period. GRACE-DSI is less accurate in drought monitoring for some periods due to the missing data, while the severity of abrupt precipitation absent in some cases can be overestimated from SPEI with big variability. This study shows the reliability and advantages of GPS data in drought monitoring.

Adjustment model and algorithm based on ellipsoid uncertainty

SONG Yingchun, XIA Yuguo, XIE Xuemei

2019, 48(5): 555-562. doi:10.11947/j.AGCS.2019.20170611

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In surveying adjustment models, there usually is some uncertain additional information or prior information on parameters, which can constraint on the parameters, and guarantee uniqueness and stability of parameters solution.In this paper, ellipsoidal sets are used to describe uncertainty, so an adjustment model with ellipsoidal uncertainty is established. The minimization in matrix trace of circumscribed ellipsoid with two ellipsoid intersections is regarded as a proposed adjustment criterion, the propagation law of uncertainty is analyzed, and the adjustment method with ellipsoid uncertainty is given. Finally, a numerical example is given to test and verify the effectiveness of the proposed algorithm, and the relation between the adjustment result and the weighted mixed estimation is illustrated.

Line segment optimization with geometric and texture constraints for high resolution optical remote sensing

DAI Jiguang, XIE Shizhe, MIAO Zhipeng, SONG Weidong, WANG Yang, ZHU Tingting

2019, 48(5): 563-571. doi:10.11947/j.AGCS.2019.20180136

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Aiming at the problem that high-resolution optical remote sensing image lines are prone to fracture, a line segment optimization algorithm is proposed. Firstly, the line segment is regarded as a way to express the contour of the ground object, and the laws of line segment fracture from two aspects of geometric features and texture features are analyzed. Secondly, the line segment optimization algorithm is proposed. It takes the results of detecting line segments as the processing primitives, determines the initial optimized line segment according to the length of the line segment, establishes the tracking rectangular region and geometric constraint model for the broken line segments,build a dynamic optimization model, and give a complete line optimization process. Through the analysis of experimental results of some actual scenes and different types of remote sensing images, it is shown that the proposed algorithm can not only solve the problem of line segment fracture caused by terrain occlusion, edge blurring and edge serration, but also comparing with other methods, the proposed algorithm has great advantages in optimizing line length and restraining over extraction problem.

An algorithm for optimizing routing of remote sensing image parallel processing based on data partitioning

FANG Lei, YAO Shenjun, BAO Hangcheng, KANG Junfeng, LIU Ting

2019, 48(5): 572-582. doi:10.11947/j.AGCS.2019.20160524

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Parallel processing technologies have been widely applied to remote sensing images processing. While previous research has developed many parallel algorithms for processing images, few studies have been focused on synchronous parallel processing for multiple computing tasks when one copy of remote sensing image has many redundant backups under the cloud computing environment. To bridge the research gap, this research proposes a routing optimization algorithm for parallel processing of remote sensing image. Based on data segmentation, the method is developed to solve the dynamic routing optimization problem when applying the parallel technology to remote sensing image distributed storage and processing. Following the introduction of 8 definitions (e.g. model data state, model elements, relative information quantity and matrix mapping) and 6 properties (e.g. directed, transitive, reproductive, multi-dimensional properties), a mathematical model is proposed. Under the framework, the ratio of average computation costs is used as the flag to control horizontal or vertical parallel processing. In addition, typical examples such as quadtree index generation, and quadtree-based target detection are presented for illustrating the application of our model on parallel processing. Finally, through the experiments, we verify the effectiveness of the algorithm, discussing the characteristics and influential factors of the algorithm.

Surface features extraction in remote sensing images based on architecture-variant CNN

WANG Huabin, HAN Min, WANG Guanghui, LI Yu

2019, 48(5): 583-596. doi:10.11947/j.AGCS.2019.20180122

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To exceed limited capacity of established convolutional neural network(CNN) with fixed architecture in traditional surface feature extraction in remote sensing images, we propose a new feature extraction method based on architecture-variant convolutional neural network (AVCNN). In AVCNN, key units are variables and the performance of the unknown model become object function. That means architecture search is added before traditional weights solving. Genetic algorithm is introduced to search proper architecture and classical algorithm is used to solve unknown weights in the candidate CNN. The CNN with final architecture is used to extract the surface feature in remote sensing images. The experiment result shows that AVCNN has flexible capacity and performances well in surface features extraction in remote sensing images.

Multi-scale fully convolutional neural network for building extraction

CUI Weihong, XIONG Baoyu, ZHANG Liyao

2019, 48(5): 597-608. doi:10.11947/j.AGCS.2019.20180062

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Some holes occurred when extracting large buildings in high spatial resolution remote sensing images with VGG16. A method of building extraction based on multi-scale features is proposed to solve this problem. Firstly, the original images were downsampled at different scales. Then, it could be extracted that the features of buildings at different scales and fused them. To reduce the number of network parameters, the fully convolutional upsampling was used to replace the fully connected layer in the original VGG16 model. The study images were from the 0.5 m resolution in Jading of Shanghai and 1 m resolution Massachusetts building dataset. The accuracy of buildings extraction were 97.09% and 96.66% respectively. The result showed the effectiveness of the proposed method.

Integration of SAR polarimetric parameters and multi-spectral data for object-based land cover classification

ZHAO Yi, JIANG Mi

2019, 48(5): 609-617. doi:10.11947/j.AGCS.2019.20170746

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An object-based approach is proposed for land cover classification using optimal polarimetric parameters. The ability to identify targets is effectively enhanced by the integration of SAR and optical images. The innovation of presented method can be summarized in the following two main points:① estimating polarimetric parameters (H-A-α decomposition) through optical image as a driver; ② a multi-resolution segmentation based on optical image only is deployed to refine classification results. The proposed method is verified by using Sentinel-1/2 datasets over Bakersfield area, California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database (NLCD). A detailed accuracy assessment complied for seven classes of surfaces shows that the proposed method outperforms the conventional approach by around 10%, with an overall accuracy of 92.6% over regions with rich texture.

Spatio-temporal modeling of city events combining datasets in cyberspace and real space

TANG Luliang, DAI Ling, REN Chang, ZHANG Xia

2019, 48(5): 618-629. doi:10.11947/j.AGCS.2019.20180327

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The scale and impacts of city events, including cultural, entertainment and sporting events, reflect the economics and culture of a city to a certain extent.The occurrence of events affects urban city significantly both online in cyberspace and offline in real space. The evolutionary perception, dynamic modeling and spatio-temporal analysis of city events from cyberspace and real space, are of important theoretical research and application value. This article proposes a novel approach of city events spatio-temporal modeling and analysis with trajectories and social media datasets in real space and cyberspace respectively. The approach firstly identifies statistically significant anomalous city regions and traffic flows with trajectories during the events, analyzing spatio-temporal change of events in real space, then analyzes spatio-temporal change during the whole process of city events in cyberspace.Finally, this article presents a modeling approach for characterizing the development and evolution of urban geospatial and behavioral space throughout events, with datasets in cyberspace and real space combined. Taking the Opus Ⅱ Jay World Tour in 2015 as an example, employing taxi GPS trace data and Weibo data in Wuhan, the proposed method realizes the whole process modeling and evolution analysis of urban geospatial and behavioral space before, during and after the event. Then the method is compared with two other approaches that use either real space dataset or cyberspace dataset alone. The experimental results show that the proposed approach measures the impact of an event both in cyberspace and real space with reason, and describes city events effectively.

The precise model of complex planar objects' topological relations

CHEN Zhanlong, YE Wen

2019, 48(5): 630-642. doi:10.11947/j.AGCS.2019.20170531

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For complex planar objects, which are composed of simple spatial objects, the existent models of topological relations may not be able to describe some topological attributes of complex objects well. Taking the topological content between complex objects into account, this paper presents a model of basic topological relations between line/planar objects, and then in which the basic topological relations and the concept of overlapping area are leveraged to describe the topological relations of simple planar objects. The definition of traversing of hole's boundary and planar with a hole are used to describe the topological relations between complex planar objects. Finally, the five basic topological relationship description modes of complex planar objects are summarized to realize description of the details of topological relations between partitions of complex planar objects.

A multisource contour matching method considering the similarity of geometric features

GUO Wenyue, LIU Haiyan, SUN Qun, YU Anzhu, DING Ziyue

2019, 48(5): 643-653. doi:10.11947/j.AGCS.2019.20170688

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The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance, while it is lack of taking the contour geometric features into account, which may lead to mismatching in map boundaries and areas with intensive contours or extreme terrain changes. In light of this, it is put forward that a matching strategy from coarse to precious based on the contour geometric features. The proposed matching strategy can be described as follows. Firstly, the point sequence is converted to feature sequence according to a feature descriptive function based on curvature and angle of normal vector.Then the level of similarity among multi-source contours is calculated by using the longest common subsequence solution. Accordingly, the identical contours could be matched based on above calculated results. In the experiment for the proposed method, the reliability and efficiency of the matching method are verified using simulative datasets and real datasets respectively. It has been proved that the proposed contour matching strategy has a high matching precision and good applicability.

TIN_DDM buffer surface construction algorithm based on rolling ball acceleration optimization model

DONG Jian, ZHANG Zhiheng, PENG Rencan, LI Gaixiao, WANG Mo

2019, 48(5): 654-667. doi:10.11947/j.AGCS.2019.20180455

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In view of the fact that the TIN_DDM buffer surface existing in the construction and application of special data type and algorithm efficiency and precision are not matching, the paper applied the rolling ball model in the process of TIN_DDM buffer surface construction. Based on the precision limitation analysis of rolling ball model, the overall precision control method of rolling ball model has been established. Considering the efficiency requirement in TIN_DDM buffer surface construction, the influence principle of key sampling points and rolling ball radius to TIN_DDM buffer surface construction efficiency has been elaborated, and the rule of identifying key sampling points has also been designed. Afterwards, by erecting the numerical relationship between key sampling points and rolling ball radius, a TIN_DDM buffer surface construction algorithm based on rolling ball acceleration optimization model has been brought forward. The time complexity of the algorithm is O(n). The experiments show that the algorithm could realize the TIN_DDM buffer surface construction with high efficiency, and the algorithm precision is controlled within 2σ.

Research on signal-in-space error anomaly detection and performance assessment of BDS satellites

FAN Lihong

2019, 48(5): 668-668. doi:10.11947/j.AGCS.2019.20180309

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