Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take ...Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship.Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit.This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps.The proposed method consists of three major steps.Firstly,the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates.Secondly,for each environmental covariate,these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area.And lastly,the extracted soil–environment relationships are applied to updating the conventional soil map with new,improved environmental data by adopting a soil land inference model(SoLIM)framework.This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County,Wisconsin,United States.The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole.Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.展开更多
This paper addresses how open geodata and crowd-sourced geodata, and the open geoportals might be integrated with the mainstream surveying and mapping practices to update traditional topomaps quickly and inexpensively...This paper addresses how open geodata and crowd-sourced geodata, and the open geoportals might be integrated with the mainstream surveying and mapping practices to update traditional topomaps quickly and inexpensively, that might be otherwise impossible to do it due to economic and logistic situations. The abundant geographic data on the internet could be used to update topographic maps while avoiding the time-consuming nature of the traditional method. To be able to use them, it is necessary to measure and quantify the quality of these data, as well as to verify their credibility, in order to incorporate them into official topographic maps. The proposed approach takes advantage of neocartography, and it’s not about further developing a new approaches, but looking differently at how data is collected, assembled controlled and been used for updating topomaps. At the beginning, the methodology used about how open geodata and crowd-sourced geodata involved in collecting, simplifying, generalizing, controlling and generating useful cartographic information that complement traditional and conventional counterparts is presented. This methodology was applied on a 1/50,000 topomap located in the north of Jeddah city (western region of Saudi Arabia), and we have demonstrated that by using this type of data, it is possible to update topographic maps quickly and at a lower cost while maintaining cartographic precision and accuracy standards.展开更多
The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation sy...The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.展开更多
自动驾驶对地图提出的高精度、高鲜度、高覆盖等要求,现阶段难以同时满足,本文针对高、低精度数据空间位置差异但特征相似度极高的特点,提出了一种将低精度观测信息转化为高精地图要素置信度的方法,在不改变高精地图更新频率的前提下,...自动驾驶对地图提出的高精度、高鲜度、高覆盖等要求,现阶段难以同时满足,本文针对高、低精度数据空间位置差异但特征相似度极高的特点,提出了一种将低精度观测信息转化为高精地图要素置信度的方法,在不改变高精地图更新频率的前提下,完善地图安全策略。该方法采用矩形邻域二级匹配原理和匹配度测量模型,缩小匹配范围和量化匹配度,从而准确匹配目标;再根据特征向量分析,判断目标要素当前状态;采用计分规则将状态转化为地图要素置信度得分。该方法运用在多省高快速高精地图置信度更新试验中,仅用普通行车记录仪图片提供的观测信息,即可更新HD地图限速标牌存在置信度,还验证了由新的观测触发和由底图更新触发两种置信度更新模式。试验结果表明,观测冗余度和置信度保持率呈正相关,当观测冗余度约为15时,可达到60 d 80%以上目标要素保持高置信,且准确率超过96%。本文方法为高精地图鲜度与安全冲突提供了一种行之有效的解决方案,可促进高精地图安全应用策略进一步深化。展开更多
基金supported by the National Natural Science Foundation of China (41431177 and 41422109)the Innovation Project of State Key Laboratory of Resources and Environmental Information System of China (O88RA20CYA)the Outstanding Innovation Team in Colleges and Universities in Jiangsu Province, China
文摘Conventional soil maps contain valuable knowledge on soil–environment relationships.Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data.Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship.Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit.This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps.The proposed method consists of three major steps.Firstly,the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates.Secondly,for each environmental covariate,these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area.And lastly,the extracted soil–environment relationships are applied to updating the conventional soil map with new,improved environmental data by adopting a soil land inference model(SoLIM)framework.This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County,Wisconsin,United States.The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole.Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.
文摘This paper addresses how open geodata and crowd-sourced geodata, and the open geoportals might be integrated with the mainstream surveying and mapping practices to update traditional topomaps quickly and inexpensively, that might be otherwise impossible to do it due to economic and logistic situations. The abundant geographic data on the internet could be used to update topographic maps while avoiding the time-consuming nature of the traditional method. To be able to use them, it is necessary to measure and quantify the quality of these data, as well as to verify their credibility, in order to incorporate them into official topographic maps. The proposed approach takes advantage of neocartography, and it’s not about further developing a new approaches, but looking differently at how data is collected, assembled controlled and been used for updating topomaps. At the beginning, the methodology used about how open geodata and crowd-sourced geodata involved in collecting, simplifying, generalizing, controlling and generating useful cartographic information that complement traditional and conventional counterparts is presented. This methodology was applied on a 1/50,000 topomap located in the north of Jeddah city (western region of Saudi Arabia), and we have demonstrated that by using this type of data, it is possible to update topographic maps quickly and at a lower cost while maintaining cartographic precision and accuracy standards.
基金Under the auspices of National High Technology Research and Development Program of China (No.2007AA12Z242)
文摘The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.
文摘自动驾驶对地图提出的高精度、高鲜度、高覆盖等要求,现阶段难以同时满足,本文针对高、低精度数据空间位置差异但特征相似度极高的特点,提出了一种将低精度观测信息转化为高精地图要素置信度的方法,在不改变高精地图更新频率的前提下,完善地图安全策略。该方法采用矩形邻域二级匹配原理和匹配度测量模型,缩小匹配范围和量化匹配度,从而准确匹配目标;再根据特征向量分析,判断目标要素当前状态;采用计分规则将状态转化为地图要素置信度得分。该方法运用在多省高快速高精地图置信度更新试验中,仅用普通行车记录仪图片提供的观测信息,即可更新HD地图限速标牌存在置信度,还验证了由新的观测触发和由底图更新触发两种置信度更新模式。试验结果表明,观测冗余度和置信度保持率呈正相关,当观测冗余度约为15时,可达到60 d 80%以上目标要素保持高置信,且准确率超过96%。本文方法为高精地图鲜度与安全冲突提供了一种行之有效的解决方案,可促进高精地图安全应用策略进一步深化。
