Acta Geodaetica et Cartographica Sinica

The new development direction of cartography promoted by spatial cognition

GAO Jun, CAO Xuefeng

2021, 50(6): 711-725. doi:10.11947/j.AGCS.2021.20210043

Asbtract ( )

HTML ( )

PDF (2322KB) ( )

References | Related Articles | Metrics

The indissoluble bond between map and cognition is continuous and deepening. The history of map can be considered as a history of spatial cognition when we review the past, and another door is opened by the theory and method of spatial cognition for cartography. The study of spatial cognition promotes the research of cartography, and to some extent, it can be considered that map is the materialization of spatial thinking function of brain. The effectiveness and value of map spatial cognition is improved by technological progress. The history of map can be divided into ancient map, ancient map, modern map and modern map stages according to the progress of human spatial cognition. In the face of the challenges about the structure of traditional disciplines posed by the wave of science and technology and social development in recent years, we should think about such a problem, Cartography needs to re-establish its own discipline system, in order to develop new cartographers using more basic knowledge, more targeted advanced technology and broader range of services.

On the mathematical basis of map spatial cognition

WAN Gang, WU Yitian

2021, 50(6): 726-738. doi:10.11947/j.AGCS.2021.20210041

Asbtract ( )

HTML ( )

PDF (1400KB) ( )

References | Related Articles | Metrics

As an important method of human spatial cognition, the emergence and development of map greatly improved the efficiency when people acquire spatial knowledge. The theory of map spatial cognition has made a series of achievements in map design, virtual geographic environment, geographic information system and new intelligent maps research. It is proposed that the research of map spatial cognition should be based on mathematical basis. This paper also clarifies and summarizes the mathematical foundation of map spatial cognition in cartography development providing a new perspective for the research of map spatial cognition.

The cognitive view of the Earth with the cases of path-finding based on Google Earth

YING Shen, ZHANG Wenbo, SU Junru, HUANG Lina

2021, 50(6): 739-748. doi:10.11947/j.AGCS.2021.20210050

Asbtract ( )

HTML ( )

PDF (23462KB) ( )

References | Related Articles | Metrics

Spatial cognition affects human spatial behaviors. The study of cognitive process is of great significance in map and navigation design, geography teaching and so on. Traditional cognitive experiments mostly use maps (including paper maps and electronic maps, street view maps, etc.) and real scenes as experimental environments to study the psychological process of subjects’ reading maps and the guidance effect of maps in real geographic environment. This paper puts forward the concept of earth view, that is, taking the third person reading scene of Google Earth as the experimental environment, studying how the candidates orientate and locate the places of countries or regions and search for the target on the Earth without fixed axis through certain operations on Google Earth, and analyzing the cognitive process of the whole earth sphere. By visualizing the process of reading the Earth with the gaze point data recorded by eye tracker and analyzing the process of thinking, it is found that on the earth, the target searching process, which combines relative position judgment and orientation positioning, is the comprehensive presentation of construction process about the candidates’ Earth view.

A naive Bayesian method for eye movement recognition of map linear elements

DONG Weihua, WANG Shengkai, WANG Xueyuan, YANG Tianyu

2021, 50(6): 749-756. doi:10.11947/j.AGCS.2021.20210048

Asbtract ( )

HTML ( )

PDF (1494KB) ( )

References | Related Articles | Metrics

At present, eye tracking technology has been widely used in human-computer interaction, user behavior recognition and prediction, but how to automatically identify user’s eye movement behavior in map reading is still a challenge. This paper proposed a method based on the naive Bayesian classification model to identify the users’ behavior when performing linear feature recognition. We first conducted an eye tracking experiment to acquire users’ eye movement dataset of map reading. Then we extracted and discretized 250 eye movement features involved in the algorithm, and used minimum redundancy maximum relevance algorithm to further select the features. The results show that when the attribute selection method is m=5 using mutual information quotient, the classification accuracy is 78.27%. And when using mutual information difference and m=4, the classification accuracy is 77.01%.We suggested that the proposed method can effectively identify the first elements in the map using eye movement data. This study explores the interaction technology by combining the eye tracking, laying the foundation for the future of designing gaze-controlled interactive map. The proposed method based on naive Bayesian model in this paper is comparable to the existing methods. In addition, the execution efficiency of the model is greatly improved due to the reduction in the number of features. The eye-track recognition algorithm of map reading behavior proposed in this study lays a foundation for future gaze-controlled interactive map research.

Shape cognition in map space using deep auto-encoder learning

YAN Xiongfeng, AI Tinghua, YANG Min, ZHENG Jianbin

2021, 50(6): 757-765. doi:10.11947/j.AGCS.2021.20210046

Asbtract ( )

HTML ( )

PDF (6105KB) ( )

References | Related Articles | Metrics

Shape is an important feature of geospatial objects and a pivotal basis for people to establish spatial concepts and form spatial cognition in map space. The study tries to integrate multiple characteristics of the shape outline using deep auto-encoder learning, and provides support for the mechanism and formalization of spatial cognition. By taking the building data as a case, the study first converts the shape outline into a sequence and extracts its descriptive characteristics by considering the local and regional structures, and then learns a shape coding from the unlabeled data using the sequence-to-sequence learning model. Experiments show that the shape cognition in map space achieves a meaningful similarity measure between different shapes by using deep auto-encoder learning. Furthermore, the shape coding can effectively represent the global and local characteristics in the application scenarios such as shape retrieval and shape matching.

The theory,map tools and development directions of geographic spatial cognition

ZHENG Shulei

2021, 50(6): 766-776. doi:10.11947/j.AGCS.2021.20210044

Asbtract ( )

HTML ( )

PDF (1185KB) ( )

References | Related Articles | Metrics

Focused on the geographic spatial cognition, this paper introduces the origination, the current situations, the four classical geographic spatial cognition theories and the difference between two factions. In the following, for the important role of map in spatial cognition, the function and research methods are concluded. Especially, the eye-tracking technology are paid more attention to, for its advantages in evaluation and interaction. Eventually, three developing directions and the characters of geographic spatial cognition in new AI era are discussed. With a focus on theoretical issues of geospatial cognition, this paper addresses at first their origin in psychology and the state of the art. The classical theories of geospatial cognition and their impacts are then introduced. Meanwhile, the fundamental difference between the geospatial cognition and geospatial sensing is pointed out. Although both are supported by the Artificial Intelligence (AI), the former is targeted to the understanding of how human brain works for spatial tasks, whereas the latter aims to maintain a dynamic digital twin of the geospace based on sensory technology and computer vision. The role and research methods of maps as a two-way tool for spatial cognition are discussed, with emphasis on eye-tracking experiments as well as their advantage in interactions. Three development trends of geospatial cognition in the era of AI—computational semantic cognition, cognitive mechanism of the mind and embodied cognition are summarized. The parallel development and characteristics of map-based spatial cognition in this same period are outlined.

An anomaly detection approach from spatio distributions of epidemic based on adjacency constraints in flow space

SHI Yan, WANG Da, CHEN Yuanfang, CHEN Bingrong, ZHAO Bingbing, DENG Min

2021, 50(6): 777-788. doi:10.11947/j.AGCS.2021.20200350

Asbtract ( )

HTML ( )

PDF (2226KB) ( )

References | Related Articles | Metrics

In view of the limitations of existing methods for detecting potential epidemic spatial anomalies caused by multiple driving factors, this paper proposes a spatial anomaly detection approach for epidemic distributions constrained by crowd flow similarities. Firstly, those epidemic attributes that are significantly associated with crowd outflow intensity from the spread center are identified using the geographic detector. Then, considering all pairs of spatial units, a spatial weight matrix is adaptively constructed by measuring the similarity of crowd outflow intensities from the spread center. Finally, each spatial unit is characterized using the local variation gradient of epidemic attribute values, based on which both global and local Moran’s I are modified to statistically discriminate the distribution patterns and detect local anomalous regions in flow space. Through performing comparative experiments on the spatio-temporal sequence of COVID-19, it illustrates that the proposed method can effectively detect the spatial anomalies caused by a variety of multiple potential factors. These findings can support the targeted epidemic prevention and control in different stages.

Classification model of ubiquitous map information facing location-based aggregation

WANG Si, WANG Guangxia, TIAN Jiangpeng

2021, 50(6): 789-799. doi:10.11947/j.AGCS.2021.20200191

Asbtract ( )

HTML ( )

PDF (4706KB) ( )

References | Related Articles | Metrics

Geographic information classification is the core content of cartography. With the coming of the ubiquitous information society, “spatio-temporal ubiquitous” is gradually becoming a new qualitative feature of geographic information, which has brought new challenges to traditional geographic information classification models. This paper takes ubiquitous map information as its research subject and puts forward a four-level information classification model of “instances→features↔dimensions→themes” to satisfy the need for location-based aggregation application. Then it designs a verifying method for the model, which tags ubiquitous maps’ thematic features based on the feature system and information dimensions, realizes the unified expression of ubiquitous map information in the vector space, and uses a hierarchical clustering algorithm to generate the classification and grading system of ubiquitous map information. At last, it verifies the feasibility of the model through a “meteorological theme” classification experiment.In essence, the model is to automatically build a classification and grading system, which is data-driven and constrained by cognitive patterns. And its feature level has extended the “instance→dimension↔theme” structure of traditional geographic information classification models, enabling ubiquitous map information classification in fine-grained semantic description while staying in the hierarchical cognitive structure.

The template matching approach to combined collinear pattern recognition in building groups

XING Ruixing, WU Fang, GONG Xianyong, DU Jiawei, LIU Chengyi

2021, 50(6): 800-811. doi:10.11947/j.AGCS.2021.20200298

Asbtract ( )

HTML ( )

PDF (14562KB) ( )

References | Related Articles | Metrics

Spatial distribution pattern recognition of buildings is significant to cartographic generalization, multi-scale representation and spatial data mining. This paper presents an approach to recognize combined collinear patterns with local heterogeneity. Firstly the cognitive characteristics and definitions of combined collinear pattern are analyzed. Then neighborhood relationship and extension alignment between buildings are obtained by clustering based on the proximity, size and orientation. Take the enlarged building’s smallest minimum bounding rectangle as the initial matching template. Finally, considering the constraints of straightness, similarity and local heterogeneity, the combined linear patterns are extracted by searching and matching buildings through continuous templates constructed based on distribution spacing and direction. Experiments show that the proposed method is effective for combined collinear pattern recognition with the agreement of human spatial cognitive characteristics.

An immune genetic algorithm to buildings displacement with constraint of safety zones

LIU Yuangang, LI Shaohua, CAI Yongxiang, HE Zhenming, MA Xiaoya, LI Pengcheng, GUO Qingsheng, HE Zongyi

2021, 50(6): 812-822. doi:10.11947/j.AGCS.2021.20200395

Asbtract ( )

HTML ( )

PDF (8123KB) ( )

References | Related Articles | Metrics

For the combinatorial optimization displacement algorithms based on heuristic search or swarm intelligence, it is a difficult problem to maintain the spatial relationship and distribution characteristics of map features. This article proposes an optimal algorithm to buildings displacement based on immune genetic algorithm (IGA) with the constraint of safety zones. In the study, the displacement problem of buildings is defined as a multi-objective optimization problem, and then the immune genetic algorithm is used to search the optimal solution. In order to keep the spatial relationship and globe spatial distribution characteristics of buildings as far as possible and avoid topology errors, Voronoi diagram and buffer areas are used to construct the displacement safety zone of each building to limit the displacement range of buildings; meanwhile, the strategy to shift the building group as a whole is used to keep local building patterns. Finally, the effectiveness of the improved algorithm is verified by taking the displacement of buildings in a block of beijing as an example. The results indicate that the algorithm can not only solve the proximity conflicts, but also keep the spatial relationship and spatial distribution characteristics of map objects.

Blockchain technology for vector geographic provenance information organization and verification

LI Hao, YUE Peng, JIANG Liangcun, ZHANG Mingda, LIANG Zheheng

2021, 50(6): 823-832. doi:10.11947/j.AGCS.2021.20200168

Asbtract ( )

HTML ( )

PDF (7100KB) ( )

References | Related Articles | Metrics

Provenance is an important research issue of “Neogeography”, and it plays a significant role in judging whether geospatial data is reliable or not. In a distributed collaborative environment, geospatial data provenance also faces reliability issues. Blockchain technology has gained rapid development in recent years due to its characteristics of credibility, transparency, and non-tampering. It provides a new solution to the reliability management of provenance records. However, how to use the blockchain to organize and store a large number of geospatial data provenance with different granularity levels remains a challenge. Therefore, taking vector data as the research object, this paper discusses the requirements in designing the structure of provenance blockchain, and proposes a method of organizing on-chain provenance information at different levels based on Merkle Patricia tree (MPT). Further, an algorithm that is suitable for the verification of vector provenance information is provided.This paper develops a vector data provenance blockchain prototype system, and conducts verification experiments using the vector provenance information. The experiments demonstrate that MPT can achieve higher performance than binary Meckel tree in vector data provenance verification.

Global refinement of building boundary with line feature constraints for stereo dense image matching

GONG Danchao, HAN Yilong, HUANG Xu

2021, 50(6): 833-846. doi:10.11947/j.AGCS.2021.20200305

Asbtract ( )

HTML ( )

PDF (21042KB) ( )

Related Articles | Metrics

Dense stereo image matching is a key technique to find correspondences through fixed matching windows and then compute 3D points through the triangulation measure. Its advantages of low cost, high point density and large measure area have fueled several smart 3D applications. However, due to occlusions in building boundaries, the fixed matching window often fattens the boundaries to a certain extend, which greatly reduces the matching accuracy in building boundaries. To achieve higher-accuracy matching result in building boundaries, this paper proposes a global building boundary refinement method based on line features, which firstly extracts line features in disparity/elevation jumps as building boundaries and then globally refines these boundaries under the basic assumption that pixels with similar intensities should have the similar disparities. The main contribution of the algorithm is to formulate the building boundary refinement problem as the optimization of a new global energy function, which is able to sharpen boundaries as well as keep details around boundaries. Compared with some state-of-the-art boundary refinement algorithms (e.g. local sharpen operators and the plane based boundary refinement), the proposed method is capable of addressing the issues they met, i.e. the incapacity to correct large errors or the over smoothness around boundaries. Experiments on aerial datasets and satellite datasets show that the proposed method is superior to two other popular boundary sharper operators and a state-of-the-art plane based boundary refinement method, and can efficiently reduce the errors in boundaries. Therefore, our method can be applied in several 3D applications, e.g. virtual reality, smart city, and building extraction.

Strain partitioning and deformation mechanism around Liupanshan tectonic zone

SU Xiaoning

2021, 50(6): 847-847. doi:10.11947/j.AGCS.2021.20200235

Asbtract ( )

HTML ( )

PDF (749KB) ( )

Related Articles | Metrics

Research of cropland soil moisture inversion method based on GNSS single antenna technology

SUN Bo

2021, 50(6): 848-848. doi:10.11947/j.AGCS.2021.20200276

Asbtract ( )

HTML ( )

PDF (755KB) ( )

Related Articles | Metrics

Big data-driven research on the interaction of human mobility pattern and urban spatial structure

CAO Jinzhou

2021, 50(6): 849-849. doi:10.11947/j.AGCS.2021.20200287

Asbtract ( )

HTML ( )

PDF (749KB) ( )

Related Articles | Metrics

Big data-driven analysis on urban activity space dynamics

GAO Qili

2021, 50(6): 850-850. doi:10.11947/j.AGCS.2021.20200310

Asbtract ( )

HTML ( )

PDF (742KB) ( )

Related Articles | Metrics

Research on the detection theory and method of crustal abnormal deformation information based on GNSS

HOU Zheng

2021, 50(6): 851-851. doi:10.11947/j.AGCS.2021.20200315

Asbtract ( )

HTML ( )

PDF (756KB) ( )

Related Articles | Metrics

Study on the crustal deformation pattern in continental regions using the space geodesy

WANG Shuai

2021, 50(6): 852-852. doi:10.11947/j.AGCS.2021.20200323

Asbtract ( )

HTML ( )

PDF (757KB) ( )

Related Articles | Metrics

Table of Content