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差分GNSS系统在大兴安岭地区森林资源调查中的精度分析     被引量:5

Differential GNSS Application on Location Precision Analysis of Forest Resource Investigation in Daxinganling Region

文献类型:期刊文献

中文题名:差分GNSS系统在大兴安岭地区森林资源调查中的精度分析

英文题名:Differential GNSS Application on Location Precision Analysis of Forest Resource Investigation in Daxinganling Region

作者:胡凯龙[1] 刘清旺[2] 穆喜云[3]

第一作者:胡凯龙

机构:[1]中国矿业大学(北京)地球科学与测绘工程学院;[2]中国林业科学研究院资源信息研究所;[3]内蒙古农业大学林学院

年份:2015

卷号:40

期号:4

起止页码:1-6

中文期刊名:林业调查规划

外文期刊名:Forest Inventory and Planning

收录:CSTPCD

基金:国家科技支撑计划课题(2012BAH34B02);国家高技术研究发展计划(2013AA12A302)

语种:中文

中文关键词:全球卫星导航系统(GNSS);森林资源调查;样地定位;定位精度;郁闭度

外文关键词:global navigation satellite system; forest resource investigation; sample plot positioning; positioning precision; canopy density

分类号:S757.2;TP39

摘要:随着全球卫星导航系统的快速发展,高精度GNSS接收机已经能够支持多卫星系统。为了确定差分GNSS系统在森林资源调查中的精度,实验布设2种不同类型的森林样地。通过具有HStar技术的GNSS接收机对样地进行精确定位,来分析差分GNSS系统的定位误差以及影响因素。结果表明:样地的定位误差与林分的郁闭度有较大关系,郁闭度越高,样地的定位精度越低;差分解的定位误差普遍在1~2 m范围内且小于单点解定位误差;由于L8样地的基准站观测数据存在多路径效应,所以其差分解误差要大于单点解误差;H-Star技术对于样地定位精度影响较小。
With the rapid development of global satellite navigation system, the high-precision GNSS re- ceivers have been able to support multi-satellite system. In order to determine the location precision of differential GNSS system in forest resource investigation, the experiment set two different types of sample plots. Through sample plots location using GNSS receivers with the H-Star technology, the research ana- lyzed the positioning error of differential GNSS system and the impact factors. Results show that sample positioning error had the larger relationship with crown density, and the higher crown density always comes with the lower positioning precision. The differential positioning errors were less than single points positioning errors and were common in the range of 1 - 2 m. Because of multipath effect from the L8 sam- ple station observation data, theL8 sample plot differential positioning error was more than single points positioning error. The effect of H-Star technology on location precision was less.

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