WO2020135585A1 - 基于互联网地图的空间数据采集方法及装置 - Google Patents
基于互联网地图的空间数据采集方法及装置 Download PDFInfo
- Publication number
- WO2020135585A1 WO2020135585A1 PCT/CN2019/128707 CN2019128707W WO2020135585A1 WO 2020135585 A1 WO2020135585 A1 WO 2020135585A1 CN 2019128707 W CN2019128707 W CN 2019128707W WO 2020135585 A1 WO2020135585 A1 WO 2020135585A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- spatial
- map
- poi
- data
- internet
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Definitions
- the invention relates to the technical field of data collection, in particular to a spatial data collection method and device based on an internet map.
- Method 1 Based on map vectors above 1:2000 and high-resolution satellite image data results and GIS (Geographic Information System) geographic platform software for artificial processing.
- GIS Geographic Information System
- Method 2 Query the place name "No. Courtyard” based on the Internet map service to get the returned attribute and spatial information.
- Method 3 Adopt suitable spatial topology calculation technology, involving spatial outlier calculation, spatial convex polygon (ConvexHull), spatial intersection operation (Intersection), spatial union operation (Union).
- Method 4 processing and processing multi-source data, multiple data with Internet maps: Baidu, Gaode, Tianmap, (OSM) open street map, these data can be referred to each other after conversion to improve data quality.
- Internet maps Baidu, Gaode, Tianmap, (OSM) open street map
- Method 1 can obtain the data of the "Hospital", it requires professional GIS platform software investment, detailed information of 1:2000 vector data, manual viewing of large amounts of data, the need for manual production is too large, it is difficult in reality Large-scale implementation.
- the method 2 can quickly obtain the place name data of the "number house”
- the spatial geometric type of the obtained spatial data is basically point data, and the specific spatial range of the "number house” is not given.
- the Internet map service The coordinates are different, and the result of obtaining spatial data is not converted, and generally cannot be used directly in other programs.
- Method 3 Although common spatial topology operations can be provided, there is no process reference for how to combine specific data operations.
- Method 4 Although multiple Internet map service data can be obtained, due to different map data characteristics, different data types and data totals, and different interface functions for secondary development, they cannot be directly mixed.
- the present invention aims to solve one of the technical problems in the related art at least to a certain extent.
- an object of the present invention is to propose a spatial data collection method based on Internet maps, which can effectively improve the practicability and applicability of data collection, with high efficiency and simple and easy implementation.
- Another object of the present invention is to propose a spatial data collection device based on Internet maps.
- an embodiment of the present invention provides a spatial data collection method based on an Internet map, including the following steps: receiving a spatial place name; calling the Internet map service Api to obtain the POI of the spatial place name according to the Internet map ( Point of Interes (point of interest) data; parse the POI data, and perform coordinate conversion on the analysis result to obtain POI coordinates; perform Union operation on the POI coordinates to obtain convex polygons; read the ones that meet the preset resolution Remotely sense the map, and find the largest circumscribed polygon of the building that intersects the convex polygon, and combine the map to show the spatial extent of the spatial place name.
- the Internet map Point of Interes (point of interest) data
- parse the POI data parse the POI data, and perform coordinate conversion on the analysis result to obtain POI coordinates
- perform Union operation on the POI coordinates to obtain convex polygons read the ones that meet the preset resolution Remotely sense the map, and find the largest circumscribed polygon of the building that intersects
- the spatial data collection method based on the Internet map of the embodiment of the present invention automatically generates the spatial data of "No. House” through Internet POI data and high-resolution remote sensing image map data to realize spatial data collection, thereby effectively improving the practicality of data collection and Applicability, high efficiency, simple and easy to implement.
- the spatial data collection method based on the Internet map according to the above embodiments of the present invention may also have the following additional technical features:
- the parsing the POI data further includes: acquiring the POI data; determining whether the POI data satisfies the parsing conditions; if the parsing conditions are satisfied, the Analysis of POI data.
- it further includes: acquiring and excluding at least one outlier according to the spatial outlier algorithm.
- the building that intersects the convex polygon to obtain the largest circumscribed polygon further includes: extracting a plurality of buildings that intersect the boundary of the convex polygon; obtaining the Shapes of multiple buildings and obtain the circumscribed rectangle of the shape.
- it further includes: detecting whether the circumscribed rectangle of the outline meets a preset condition; if the preset condition is not satisfied, adjusting the weight of the convex vertex of the circumscribed rectangle.
- an internet map-based spatial data collection device including: a receiving module for receiving spatial place names; a calling module for calling the Internet map service Api (Application Programming Interface) , Application programming interface) to obtain the POI data of the spatial place name according to the Internet map; the parsing module is used to parse the POI data and perform coordinate conversion on the parsing result to obtain POI coordinates; the operation module is used to Perform a Union operation on the POI coordinates to obtain a convex polygon; a reading module is used to read a remote sensing map that satisfies a preset resolution, and obtain the largest external polygon for a building that intersects the convex polygon, and combine the map Show the spatial extent of the spatial place names.
- a receiving module for receiving spatial place names
- a calling module for calling the Internet map service Api (Application Programming Interface) , Application programming interface) to obtain the POI data of the spatial place name according to the Internet map
- the parsing module is used to parse the PO
- the spatial data collection device based on the Internet map of the embodiment of the present invention can automatically generate the spatial data of "No. House” through Internet POI data and high-resolution remote sensing image map data to realize the spatial data collection, thereby effectively improving the practicality of data collection and Applicability, high efficiency, simple and easy to implement.
- the spatial data collection device based on the Internet map may also have the following additional technical features:
- the parsing module is further used to obtain the POI data, and determine whether the POI data meets the parsing conditions, and when the parsing conditions are met, the POI data For analysis.
- it further includes: a culling module, configured to acquire and eliminate at least one outlier according to the spatial outlier algorithm.
- the reading module is further used to extract multiple buildings that intersect the boundary of the convex polygon, and obtain the outlines of the multiple buildings, and obtain all The circumscribed rectangle of the outline.
- it further includes: a detection module, configured to detect whether the circumscribed rectangle of the shape meets a preset condition, and adjust the weight to adjust the circumscribed rectangle when the preset condition is not met. Vertex of the convex edge.
- FIG. 1 is a flowchart of a spatial data collection method based on an Internet map according to an embodiment of the present invention
- FIG. 2 is a flowchart of a spatial data collection method based on an Internet map according to a specific embodiment of the present invention
- FIG. 3 is a schematic structural diagram of a spatial data collection device based on an Internet map according to an embodiment of the present invention.
- FIG. 1 is a flowchart of a spatial data collection method based on an Internet map according to an embodiment of the present invention.
- the spatial data collection method based on the Internet map includes the following steps:
- step S101 a spatial place name is received.
- the spatial place name may be the place name of “No. Courtyard”.
- the embodiment of the present invention inputs the place name including “No. Courtyard”.
- the corresponding relationship between the address of "No. Courtyard” and the classification of place names is as follows:
- step S102 the Internet map service Api is called to obtain the POI data of the spatial place name according to the Internet map.
- the program calls a specific Internet map service Api.
- the embodiment of the present invention obtains map POI data based on the Internet map service SDK Api.
- step S103 the POI data is analyzed, and the analysis result is coordinate-transformed to obtain POI coordinates.
- parsing POI data further includes: obtaining POI data; judging whether the POI data satisfies the parsing conditions; if the parsing conditions are satisfied, parsing the POI data.
- the parsing condition may be that the number of returned POI data is greater than a preset value, for example, when more than three POI data are parsed, of course, those skilled in the art can set a preset value according to the actual situation, for example, Analysis is performed when there are more than 5 POI data, which is not specifically limited here. In the embodiment of the present invention, analysis is performed when there are more than 3 POI data. For example, as shown in FIG. 2, the embodiment of the present invention can parse the returned more than 3 POI data and perform necessary coordinate conversion.
- step S104 perform Union operation on the POI coordinates to obtain a convex polygon.
- it further includes: acquiring and excluding at least one outlier according to the spatial outlier algorithm.
- the embodiment of the present invention processes the POI coordinates and proposes abnormal data to retain the normal data.
- the embodiment of the present invention can be found according to the spatial outlier search algorithm, Eliminate outliers, perform Union operation on POI coordinates to obtain a convex polygon, where the convex polygon can be represented by Z1.
- the embodiment of the present invention stores the convex polygon, which is an initial address space library.
- step S105 a remote sensing map satisfying a preset resolution is read, and the largest circumscribed polygon is obtained for the building that intersects the convex polygon, and the spatial range of the spatial place name is displayed in conjunction with the map.
- the preset resolution may be a resolution higher than 1 meter, and of course, it may be other resolutions, for example, a resolution higher than 2 meters. Those skilled in the art may set it according to actual conditions. This is not specifically limited.
- a remote sensing map with a resolution higher than 1 meter is used as an example.
- the remote sensing map with a resolution higher than 1 meter may be referred to as a high-resolution remote sensing map, that is, the embodiment of the present invention reads high resolution Remote sensing maps, buildings where convex polygons intersect to find the largest circumscribed polygon, in this case, the final address space library.
- the building that intersects the convex polygon to obtain the largest circumscribed polygon further includes: extracting a plurality of buildings that intersect the boundary of the convex polygon; obtaining the shapes of the plurality of buildings, and Get the circumscribed rectangle of the shape.
- it further includes: detecting whether the circumscribed rectangle of the outline meets the preset condition; if the preset condition is not satisfied, adjusting the weight of the convex vertex of the circumscribed rectangle.
- the embodiments of the present invention formulate place name codes according to the "GBT 18521-2001 Place Name Classification and Category Code Preparation Rules", using the Internet map service of Tian Map, Baidu Map, Gaode Map and place name data, POI data, high-resolution remote sensing images
- the full-band image is processed into a series of planar spatial data data of the place name "No. Courtyard”.
- the embodiments of the present invention may also process data into spatial data of addresses based on the GIS platform.
- the embodiment of the present invention uses the address achievement mode to support the offline and online modes, and uses a program to automatically process and input the spatial range of names of the "No. courtyard” type.
- the "No. House” spatial data is automatically generated through Internet POI data and high-resolution remote sensing image map data to realize spatial data collection, thereby effectively improving the practicality of data collection High efficiency and easy to implement.
- FIG. 3 is a schematic structural diagram of a spatial data collection device based on an Internet map according to an embodiment of the present invention.
- the spatial data collection device 10 based on the Internet map includes a receiving module 100, a calling module 200, a parsing module 300, an arithmetic module 400, and a reading module 500.
- the receiving module 100 is used to receive spatial place names.
- the calling module 200 is used to call the Internet map service Api to obtain the POI data of the spatial place name according to the Internet map.
- the parsing module 300 is used for parsing POI data, and performing coordinate conversion on the parsing result to obtain POI coordinates.
- the operation module 400 is used for performing Union operation on POI coordinates to obtain convex polygons.
- the reading module 500 is used to read a remote sensing map satisfying a preset resolution, find the largest circumscribed polygon of the building that intersects the convex polygon, and combine the map to show the spatial scope of the spatial place name.
- the device 10 of the embodiment of the invention effectively improves the practicability and applicability of data collection, has high efficiency, and is simple and easy to implement.
- the parsing module 300 is further used to obtain POI data, and determine whether the POI data meets the parsing conditions, and when the parsing conditions are satisfied, analyze the POI data.
- the device 10 of the embodiment of the present invention further includes: a rejection module.
- the rejection module is used to obtain and remove at least one outlier according to the spatial outlier algorithm.
- the reading module 500 is further used to extract multiple buildings intersecting the boundary of the convex polygon, and obtain the outer shapes of the multiple buildings, and obtain the circumscribed rectangles of the outer shapes.
- the apparatus 10 of the embodiment of the present invention further includes: a detection module.
- the detection module is used to detect whether the circumscribed rectangle of the shape meets the preset condition, and when the preset condition is not satisfied, the weight adjusts the convex vertex of the circumscribed rectangle.
- the "No. House” spatial data is automatically generated through Internet POI data and high-resolution remote sensing image map data to realize spatial data collection, thereby effectively improving the practicality of data collection High efficiency and easy to implement.
- first and second are used for description purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
- the features defined as “first” and “second” may include at least one of the features explicitly or implicitly.
- the meaning of “plurality” is at least two, such as two, three, etc., unless specifically defined otherwise.
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Processing Or Creating Images (AREA)
- Instructional Devices (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
一种基于互联网地图的空间数据采集方法及装置,其中,方法包括以下步骤:接收空间地名(S101);调用互联网地图服务Api,以根据互联网地图得到空间地名的POI数据(S102);解析POI数据,并对解析结果进行坐标转换,以得到POI坐标(S103);对POI坐标进行Union运算,以获取凸多边形(S104);读取满足预设分辨率的遥感地图,并对与凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现空间地名的空间范围(S105)。该方法通过互联网POI数据和高分辨率遥感影像地图数据自动化生成"号院"空间数据,以实现空间数据采集,从而有效提高数据采集的实用性和适用性,效率高,简单易实现。
Description
相关申请的交叉引用
本申请要求北京辰安科技股份有限公司、清华大学于2018年12月29日提交的、发明名称为“基于互联网地图的空间数据采集方法及装置”的、中国专利申请号“201811642843.6”的优先权。
本发明涉及数据采集技术领域,特别涉及一种基于互联网地图的空间数据采集方法及装置。
目前,“丰秀中路3号院”地名中“号院”空间几何类型大多数用点数据标示,实际上“号院”在人们意识中包含有范围,这里空间几何类型显然需要用面状来描述,但是现实中却没有完全按照面去采集和存储。
相关技术中,(1)方法1:基于比例尺1:2000以上地图矢量和高分辨率卫星影像数据成果和GIS(Geographic Information System,地理信息系统)平台软件进行人为加工制作。
(2)方法2:基于互联网地图服务查询出地名“号院”,得到返回的属性和空间信息。
(3)方法3:采用适合的空间拓扑运算技术,涉及空间离群点计算,空间凸多边形(ConvexHull),空间交集运算(Intersection),空间并集运算(Union)。
(4)方法4:处理和加工多来源数据,有互联网地图的多家数据:百度,高德,天地图,(OSM)开放街图,这些数据可以经过转换后可以互相参考,提高数据质量。
然而,方法1虽然可以得到“号院”范围数据,但是需要专业的GIS平台软件投入,1:2000矢量数据详尽信息,人工查看数据量大,需要手工制作工作量太大,很难在现实中进行大范围实现。同样地,方法2虽然可以快速获取“号院”的地名数据,但是获取的空间数据的空间几何类型基本上为点数据,没有给出具体的“号院”的空间范围,另外由于互联网地图服务坐标不同,获得空间数据结果没有转换,一般不能直接用于其它程序上。方法3:虽然可以提供常用的空间拓扑运算,但是对于具体数据如何组合运算是没有流程借鉴的。方法4:虽然可以得到多家互联网地图服务数据,由于各家地图数据特色不同、数据种类和数据总量不同、二次开发的接口函数不同,从而不能直接混合使用。
发明内容
本发明旨在至少在一定程度上解决相关技术中的技术问题之一。
为此,本发明的一个目的在于提出一种基于互联网地图的空间数据采集方法,该方法可以有效提高数据采集的实用性和适用性,效率高,简单易实现。
本发明的另一个目的在于提出一种基于互联网地图的空间数据采集装置。
为达到上述目的,本发明一方面实施例提出了一种基于互联网地图的空间数据采集方法,包括以下步骤:接收空间地名;调用互联网地图服务Api,以根据互联网地图得到所述空间地名的POI(Point of Interes,兴趣点)数据;解析所述POI数据,并对解析结果进行坐标转换,以得到POI坐标;对所述POI坐标进行Union运算,以获取凸多边形;读取满足预设分辨率的遥感地图,并对与所述凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现所述空间地名的空间范围。
本发明实施例的基于互联网地图的空间数据采集方法,通过互联网POI数据和高分辨率遥感影像地图数据自动化生成“号院”空间数据,以实现空间数据采集,从而有效提高数据采集的实用性和适用性,效率高,简单易实现。
另外,根据本发明上述实施例的基于互联网地图的空间数据采集方法还可以具有以下附加的技术特征:
进一步地,在本发明的一个实施例中,所述解析所述POI数据,进一步包括:获取所述POI数据;判断所述POI数据是否满足解析条件;如果满足所述解析条件,则对所述POI数据进行解析。
进一步地,在本发明的一个实施例中,还包括:根据空间离群点算法获取并剔除至少一个离群点。
进一步地,在本发明的一个实施例中,所述与所述凸多边形相交的建筑物进行求最大外接多边形,进一步包括:提取与所述凸多边形的边界相交的多个建筑物;获取所述多个建筑物的外形,并获取所述外形的外接矩形。
进一步地,在本发明的一个实施例中,还包括:检测所述外形的外接矩形是否满足预设条件;如果不满足所述预设条件,则权重调整所述外接矩形的凸边形顶点。
为达到上述目的,本发明另一方面实施例提出了一种基于互联网地图的空间数据采集装置,包括:接收模块,用于接收空间地名;调用模块,用于调用互联网地图服务Api(Application Programming Interface,应用程序编程接口),以根据互联网地图得到所述空间地名的POI数据;解析模块,用于解析所述POI数据,并对解析结果进行坐标转换,以得到POI坐标;运算模块,用于对所述POI坐标进行Union运算,以获取凸多边形;读取模块,用于读取满足预设分辨率的遥感地图,并对与所述凸多边形相交的建筑物进行求最 大外接多边形,并结合地图展现所述空间地名的空间范围。
本发明实施例的基于互联网地图的空间数据采集装置,通过互联网POI数据和高分辨率遥感影像地图数据自动化生成“号院”空间数据,以实现空间数据采集,从而有效提高数据采集的实用性和适用性,效率高,简单易实现。
另外,根据本发明上述实施例的基于互联网地图的空间数据采集装置还可以具有以下附加的技术特征:
进一步地,在本发明的一个实施例中,所述解析模块进一步用于获取所述POI数据,且判断所述POI数据是否满足解析条件,并在满足所述解析条件时,对所述POI数据进行解析。
进一步地,在本发明的一个实施例中,还包括:剔除模块,用于根据空间离群点算法获取并剔除至少一个离群点。
进一步地,在本发明的一个实施例中,所述读取模块进一步地用于提取与所述凸多边形的边界相交的多个建筑物,并获取所述多个建筑物的外形,并获取所述外形的外接矩形。
进一步地,在本发明的一个实施例中,还包括:检测模块,用于检测所述外形的外接矩形是否满足预设条件,并在不满足所述预设条件时,权重调整所述外接矩形的凸边形顶点。
本发明附加的方面和优点将在下面的描述中部分给出,部分将从下面的描述中变得明显,或通过本发明的实践了解到。
本发明上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解,其中:
图1为根据本发明一个实施例的基于互联网地图的空间数据采集方法的流程图;
图2为根据本发明一个具体实施例的基于互联网地图的空间数据采集方法的流程图;
图3为根据本发明一个实施例的基于互联网地图的空间数据采集装置的结构示意图。
下面详细描述本发明的实施例,所述实施例的示例在附图中示出,其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的,旨在用于解释本发明,而不能理解为对本发明的限制。
下面参照附图描述根据本发明实施例提出的基于互联网地图的空间数据采集方法及装置,首先将参照附图描述根据本发明实施例提出的基于互联网地图的空间数据采集方 法。
图1是本发明一个实施例的基于互联网地图的空间数据采集方法的流程图。
如图1所示,该基于互联网地图的空间数据采集方法包括以下步骤:
在步骤S101中,接收空间地名。
可以理解的是,空间地名可以为“号院”的地名,如图2所示,首先,本发明实施例输入包含“号院”的地名。其中,“号院”地址和地名分类中对应关系如下:
在步骤S102中,调用互联网地图服务Api,以根据互联网地图得到空间地名的POI数据。
可以理解的是,程序调用具体的互联网地图服务Api,比如,如图2所示,本发明实施例基于互联网地图服务SDK Api获取地图POI数据。
在步骤S103中,解析POI数据,并对解析结果进行坐标转换,以得到POI坐标。
其中,在本发明的一个实施例中,解析POI数据,进一步包括:获取POI数据;判断POI数据是否满足解析条件;如果满足解析条件,则对POI数据进行解析。
可以理解的是,解析条件可以为返回的POI数据的数量大于预设值,比如,大于3个以上的POI数据时进行解析,当然,本领域技术人员可以根据实际情况设置预设值,比如,大于5个以上的POI数据时进行解析,在此不做具体限定。本发明实施例以大于3个以上的POI数据时进行解析为例,例如,如图2所示,本发明实施例可以解析返回的大于3个以上的POI数据,进行必要的坐标转换。
在步骤S104中,对POI坐标进行Union运算,以获取凸多边形。
其中,在本发明的一个实施例中,还包括:根据空间离群点算法获取并剔除至少一个离群点。
可以理解的是,本发明实施例对于得到POI坐标进行处理,提出非正常数据,以保留正常数据,具体地,如图2所示,本发明实施例可以根据空间离群点查找算法找出来,剔除离群点,对于POI的坐标进行Union运算,获取一个凸多边形,其中,凸多边形可以用Z1表示。另外,在获取得到凸多边形之后,本发明实施例对该凸多边形进行存储,此时为初始地址空间库。
在步骤S105中,读取满足预设分辨率的遥感地图,并对与凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现空间地名的空间范围。
可以理解的是,预设分辨率可以为高于1米的分辨率,当然,也可以为其他分辨率, 比如,高于2米的分辨率,本领域技术人员可以根据实际情况进行设置,在此不做具体限定。本发明实施例以高于1米的分辨率的遥感地图为例,高于1米的分辨率的遥感地图可以称为为高分辨率遥感地图,也就是说,本发明实施例读取高分辨遥感地图,凸多边形相交的建筑物进行求最大外接多边形,此时,为最终地址空间库。
进一步地,在本发明的一个实施例中,与凸多边形相交的建筑物进行求最大外接多边形,进一步包括:提取与凸多边形的边界相交的多个建筑物;获取多个建筑物的外形,并获取外形的外接矩形。
举例而言,读取高分辨率遥感地图,提取跟Z1边界相交的建筑物n个,求n个建筑物的外形m(n),求m(n)的外接矩形Z2,地图叠加显示POI、遥感地图和计算的Z2多变形结果。
进一步地,在本发明的一个实施例中,还包括:检测外形的外接矩形是否满足预设条件;如果不满足预设条件,则权重调整外接矩形的凸边形顶点。
可以理解的是,如图2所示,人工根据运算结果,进行评估后,如果不符合真实情况,可以进行调整Z2的凸边形顶点。
具体而言,读取外接多边形周边的高分辨率遥感地图;解译高分辨率遥感地图范围内所有建筑物构成的凸多边形集合;获取凸多边形集合和外接矩形的交集,以根据交集检测的外接矩形是否满足预设条件,并在不满足预设条件时进行人工干预,从而实现对外接矩形的凸边形顶点的调整。综上,本发明实施例依据《GBT 18521-2001 地名分类与类别代码编制规则》制定地名编码,利用天地图、百度地图、高德地图互联网地图服务和地名数据、POI数据、高分辨率遥感影全波段像,经过一系列的加工成地名“号院”的面状空间数据数据。另外,本发明实施例也可以基于GIS平台进行数据加工成地址的空间数据。本发明实施例使用地址成果模式支持离线和在线模式,并且采用程序自动化加工输入“号院”类型地名的空间范围。
根据本发明实施例提出的基于互联网地图的空间数据采集方法,通过互联网POI数据和高分辨率遥感影像地图数据自动化生成“号院”空间数据,以实现空间数据采集,从而有效提高数据采集的实用性和适用性,效率高,简单易实现。
其次参照附图描述根据本发明实施例提出的基于互联网地图的空间数据采集装置。
图3是本发明一个实施例的基于互联网地图的空间数据采集装置的结构示意图。
如图3所示,该基于互联网地图的空间数据采集装置10包括:接收模块100、调用模块200、解析模块300、运算模块400和读取模块500。
其中,接收模块100用于接收空间地名。调用模块200用于调用互联网地图服务Api,以根据互联网地图得到空间地名的POI数据。解析模块300用于解析POI数据,并对解析 结果进行坐标转换,以得到POI坐标。运算模块400用于对POI坐标进行Union运算,以获取凸多边形。读取模块500用于读取满足预设分辨率的遥感地图,并对与凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现空间地名的空间范围。本发明实施例的装置10有效提高数据采集的实用性和适用性,效率高,简单易实现。
进一步地,在本发明的一个实施例中,解析模块300进一步用于获取POI数据,且判断POI数据是否满足解析条件,并在满足解析条件时,对POI数据进行解析。
进一步地,在本发明的一个实施例中,本发明实施例的装置10还包括:剔除模块。其中,剔除模块用于根据空间离群点算法获取并剔除至少一个离群点。
进一步地,在本发明的一个实施例中,读取模块500进一步地用于提取与凸多边形的边界相交的多个建筑物,并获取多个建筑物的外形,并获取外形的外接矩形。
进一步地,在本发明的一个实施例中,本发明实施例的装置10还包括:检测模块。其中,检测模块用于检测外形的外接矩形是否满足预设条件,并在不满足预设条件时,权重调整外接矩形的凸边形顶点。
需要说明的是,前述对基于互联网地图的空间数据采集方法实施例的解释说明也适用于该实施例的基于互联网地图的空间数据采集装置,此处不再赘述。
根据本发明实施例提出的基于互联网地图的空间数据采集装置,通过互联网POI数据和高分辨率遥感影像地图数据自动化生成“号院”空间数据,以实现空间数据采集,从而有效提高数据采集的实用性和适用性,效率高,简单易实现。
此外,术语“第一”、“第二”仅用于描述目的,而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此,限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本发明的描述中,“多个”的含义是至少两个,例如两个,三个等,除非另有明确具体的限定。
在本说明书的描述中,参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中,对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且,描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外,在不相互矛盾的情况下,本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
尽管上面已经示出和描述了本发明的实施例,可以理解的是,上述实施例是示例性的,不能理解为对本发明的限制,本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。
Claims (10)
- 一种基于互联网地图的空间数据采集方法,其特征在于,包括以下步骤:接收空间地名;调用互联网地图服务Api,以根据互联网地图得到所述空间地名的POI数据;解析所述POI数据,并对解析结果进行坐标转换,以得到POI坐标;对所述POI坐标进行Union运算,以获取凸多边形;以及读取满足预设分辨率的遥感地图,并对与所述凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现所述空间地名的空间范围。
- 根据权利要求1所述的基于互联网地图的空间数据采集方法,其特征在于,所述解析所述POI数据,进一步包括:获取所述POI数据;判断所述POI数据是否满足解析条件;如果满足所述解析条件,则对所述POI数据进行解析。
- 根据权利要求1所述的基于互联网地图的空间数据采集方法,其特征在于,还包括:根据空间离群点算法获取并剔除至少一个离群点。
- 根据权利要求1所述的基于互联网地图的空间数据采集方法,其特征在于,所述与所述凸多边形相交的建筑物进行求最大外接多边形,进一步包括:提取与所述凸多边形的边界相交的多个建筑物;获取所述多个建筑物的外形,并获取所述外形的外接矩形。
- 根据权利要求4所述的基于互联网地图的空间数据采集方法,其特征在于,还包括:检测所述外形的外接矩形是否满足预设条件;如果不满足所述预设条件,则权重调整所述外接矩形的凸边形顶点。
- 一种基于互联网地图的空间数据采集装置,其特征在于,包括:接收模块,用于接收空间地名;调用模块,用于调用互联网地图服务Api,以根据互联网地图得到所述空间地名的POI数据;解析模块,用于解析所述POI数据,并对解析结果进行坐标转换,以得到POI坐标;运算模块,用于对所述POI坐标进行Union运算,以获取凸多边形;以及读取模块,用于读取满足预设分辨率的遥感地图,并对与所述凸多边形相交的建筑物进行求最大外接多边形,并结合地图展现所述空间地名的空间范围。
- 根据权利要求6所述的基于互联网地图的空间数据采集装置,其特征在于,所述解 析模块进一步用于获取所述POI数据,且判断所述POI数据是否满足解析条件,并在满足所述解析条件时,对所述POI数据进行解析。
- 根据权利要求6所述的基于互联网地图的空间数据采集装置,其特征在于,还包括:剔除模块,用于根据空间离群点算法获取并剔除至少一个离群点。
- 根据权利要求6所述的基于互联网地图的空间数据采集装置,其特征在于,所述读取模块进一步地用于提取与所述凸多边形的边界相交的多个建筑物,并获取所述多个建筑物的外形,并获取所述外形的外接矩形。
- 根据权利要求9所述的基于互联网地图的空间数据采集装置,其特征在于,还包括:检测模块,用于检测所述外形的外接矩形是否满足预设条件,并在不满足所述预设条件时,权重调整所述外接矩形的凸边形顶点。
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811642843.6 | 2018-12-29 | ||
| CN201811642843.6A CN109783591B (zh) | 2018-12-29 | 2018-12-29 | 基于互联网地图的空间数据采集方法及装置 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2020135585A1 true WO2020135585A1 (zh) | 2020-07-02 |
Family
ID=66499581
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2019/128707 Ceased WO2020135585A1 (zh) | 2018-12-29 | 2019-12-26 | 基于互联网地图的空间数据采集方法及装置 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN109783591B (zh) |
| WO (1) | WO2020135585A1 (zh) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109783591B (zh) * | 2018-12-29 | 2021-09-03 | 北京辰安科技股份有限公司 | 基于互联网地图的空间数据采集方法及装置 |
| CN110427450A (zh) * | 2019-08-09 | 2019-11-08 | 深圳四维集思技术服务有限公司 | 基于互联网地图的油气管线数据处理方法和系统 |
| CN112925764B (zh) * | 2019-12-10 | 2023-09-12 | 中国再保险(集团)股份有限公司 | 一种巨灾模型的行业风险暴露数据库及其构建方法 |
| CN112163062B (zh) * | 2020-10-21 | 2022-10-21 | 腾讯科技(深圳)有限公司 | 数据处理方法、装置、计算机设备及存储介质 |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060041375A1 (en) * | 2004-08-19 | 2006-02-23 | Geographic Data Technology, Inc. | Automated georeferencing of digitized map images |
| CN103150309A (zh) * | 2011-12-07 | 2013-06-12 | 清华大学 | 一种空间方向感知地图兴趣点搜索方法和系统 |
| CN104282221A (zh) * | 2013-07-01 | 2015-01-14 | 北京四维图新科技股份有限公司 | 一种构建室内地图的道路网络的方法 |
| CN104484790A (zh) * | 2014-12-26 | 2015-04-01 | 清华大学深圳研究生院 | 一种物流业务的地址匹配方法及装置 |
| CN105404685A (zh) * | 2015-12-09 | 2016-03-16 | 中国农业银行股份有限公司 | 一种电子地图空间查询方法及系统 |
| CN109783591A (zh) * | 2018-12-29 | 2019-05-21 | 北京辰安科技股份有限公司 | 基于互联网地图的空间数据采集方法及装置 |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102902837B (zh) * | 2012-07-25 | 2015-02-11 | 南京大学 | 一种复杂矢量多边形图形空间叠置分析制图方法 |
| CN103258007B (zh) * | 2013-04-16 | 2019-02-01 | 中国科学院地理科学与资源研究所 | 一种利用冲突检测机制的地图标注方法及装置 |
| CN103617295B (zh) * | 2013-12-16 | 2017-09-08 | 北京锐安科技有限公司 | 一种地理信息矢量数据处理的方法和装置 |
| US10231084B2 (en) * | 2015-08-14 | 2019-03-12 | Aeris Communications, Inc. | System and method for monitoring devices relative to a learned geographic area |
| CN105512169B (zh) * | 2016-03-10 | 2018-05-15 | 珠海市规划设计研究院 | 基于路径和权的最短路径搜索方法 |
| CN106529794A (zh) * | 2016-10-28 | 2017-03-22 | 上海金智晟东电力科技有限公司 | 一种配电网故障波及范围可视化方法及系统 |
-
2018
- 2018-12-29 CN CN201811642843.6A patent/CN109783591B/zh active Active
-
2019
- 2019-12-26 WO PCT/CN2019/128707 patent/WO2020135585A1/zh not_active Ceased
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060041375A1 (en) * | 2004-08-19 | 2006-02-23 | Geographic Data Technology, Inc. | Automated georeferencing of digitized map images |
| CN103150309A (zh) * | 2011-12-07 | 2013-06-12 | 清华大学 | 一种空间方向感知地图兴趣点搜索方法和系统 |
| CN104282221A (zh) * | 2013-07-01 | 2015-01-14 | 北京四维图新科技股份有限公司 | 一种构建室内地图的道路网络的方法 |
| CN104484790A (zh) * | 2014-12-26 | 2015-04-01 | 清华大学深圳研究生院 | 一种物流业务的地址匹配方法及装置 |
| CN105404685A (zh) * | 2015-12-09 | 2016-03-16 | 中国农业银行股份有限公司 | 一种电子地图空间查询方法及系统 |
| CN109783591A (zh) * | 2018-12-29 | 2019-05-21 | 北京辰安科技股份有限公司 | 基于互联网地图的空间数据采集方法及装置 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109783591B (zh) | 2021-09-03 |
| CN109783591A (zh) | 2019-05-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US12242704B2 (en) | System and method of indicating the distance or the surface of an image of a geographical object | |
| TWI546519B (zh) | 興趣點的展現方法及裝置 | |
| US9418472B2 (en) | Blending between street view and earth view | |
| EP3664040A1 (en) | Information processing device, authoring method, and program | |
| KR20220054754A (ko) | 시선 추적 방법, 장치, 모델 트레이닝 방법 및 장치, 단말 기기, 컴퓨터 판독 가능한 저장 매체 및 컴퓨터 프로그램 | |
| US20190221023A1 (en) | Determining and Presenting Solar Flux Information | |
| CN109783591B (zh) | 基于互联网地图的空间数据采集方法及装置 | |
| TW201250608A (en) | Image comparison system and method | |
| CN115982824B (zh) | 施工现场工人空间管理方法、装置、电子设备及存储介质 | |
| CN112288672B (zh) | 肿瘤检测方法及肿瘤检测装置 | |
| CN108375807A (zh) | 气象数据的获取方法及装置 | |
| CN112489099A (zh) | 点云配准方法、装置、存储介质及电子设备 | |
| CN104867181A (zh) | 气象元素在三维地球模型的快速显示和绘制方法 | |
| WO2024088071A1 (zh) | 三维场景重建方法、装置、设备及存储介质 | |
| CN114565722A (zh) | 一种三维模型单体化实现方法 | |
| Tu et al. | Detecting building facade damage from oblique aerial images using local symmetry feature and the GINI index | |
| US20150154228A1 (en) | Hierarchical spatial clustering of photographs | |
| LU507672B1 (en) | Generation method and apparatus of public interest litigation clue and storage medium | |
| JP2010506337A (ja) | 現実の世界の3−d空間データを可視化及び測定するためのシステム及び方法 | |
| CN116524143A (zh) | 一种gis地图构建方法 | |
| Pyka et al. | LiDAR-based method for analysing landmark visibility to pedestrians in cities: case study in Kraków, Poland | |
| CN117932100A (zh) | 一种基于气象海洋信息的可视化方法和系统 | |
| CN116416403A (zh) | 基于遥感影像的建筑工地施工进程监测方法及系统 | |
| WO2013134108A1 (en) | Non-photorealistic rendering of geographic features in a map | |
| CN117557734A (zh) | 三维建筑模型展示以及生成方法、装置和存储介质 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 19901656 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 19901656 Country of ref document: EP Kind code of ref document: A1 |
