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Key technology of mine underground mobile positioning based on LiDAR and coded sequence pattern

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中国有色金属学会会刊：英文版 2011年第S3期21卷 570-576页

作者： WANG Zhi1, 2. WU Li-xin1, 2. LI Hui-ying3.1. College of Resources and civil Engineering, Northeastern University, Shenyang 110004,{2. 2. {2. of {3. reduction and emergency management, ministry of civil affairs and ministry of {12., beijing Normal University,{13.,{2. 3. College of Computer Science and Technology, Jilin University, Changchun 13.012.{2. [a] College of Resources and civil Engineering Northeastern University Shenyang 110004 China [b] academy of disaster {2. and {3. management Ministry of Civil Affairs and Ministry of Education Beijing Normal University Beijing 100875 China [c] College of Computer Science and Technology Jilin University Changchun 130012 China

Technologies of underground mobile positioning were proposed based on LiDAR data and coded sequence pattern landmarks for mine shafts and tunnels environment to meet the needs of fast and accurate positioning and navigation of equipments in the mine underground without satellite navigation signals. A coded sequence pattern was employed for automatic matching of 3. scans. The methods of SIFT feature, Otsu segmentation and fast hough transformation were described for the identification, positioning and interpretation of the coded sequence patterns, respectively. The POSIT model was presented for speeding up computation of the translation and rotation parameters of LiDAR point data, so as to achieve automatic 3. mapping of mine shafts and tunnels. The moving positioning experiment was applied to evaluating the accuracy of proposed pose estimation method from LiDAR scans and coded sequence pattern landmarks acquired in an indoor environment. The performance was evaluated using ground truth data of the indoor setting so as to measure derivations with six degrees of freedom.

关键词： LiDAR coded sequence pattern mobile positioning SLAM algorithm POSIT algorithm

Spatial patterns of ecosystem carbon residence time in Chinese forests

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中国科学：地球科学英文版 2010年第8期53卷 1229-1240页

作者： ZHOU Tao1,2. SHI PeiJun1,2. JIA GenSuo3. LI XiuJuan1,2.& LUO YiQi4 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, beijing Normal University,{2.,{2. 2.{3. of disaster reduction and emergency management, ministry of civil affairs & ministry of education,{2.,{2. 3.Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Chinese {3. of Sciences, beijing 10002.,{2. 4 Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73.19, USA 1. State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Beijing 100875 China2. Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs & Ministry of Education Beijing 100875 China3. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia Chinese Academy of Sciences Beijing 100029 China4. Department of Botany and Microbiology University of Oklahoma Norman OK 73019 USA

Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over china, with most of regions having values between 2. and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3.years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (3..1 and 3..3.years, respectively), and the evergreen broadleaf forest had the lowest value (3..7 years). The averaged carbon residence time of forest ecosystems in china was 57.8 years.

关键词： carbon residence time carbon cycle forest ecosystem data-model fusion inverse modeling genetic algorithm

Spatial patterns in temperature sensitivity of soil respiration in china: Estimation with inverse modeling

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Science china(Life Sciences) 2009年第10期52卷 982-989页

作者： ZHOU Tao1,2. SHI PeiJun1,2. HUI DaFeng3.& LUO YiQi4 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, beijing Normal University,{2.,{2. 2.{3. of disaster reduction and emergency management, ministry of civil affairs & ministry of education,{2.,{2. 3.Department of Biological Sciences, Tennessee State University, Nashville, TN 3.2.9, USA 4 Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73.19, USA 1. State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Beijing 100875 China 2. academy of disaster {2. and {3. management Ministry of Civil Affairs & Ministry of Education Beijing 100875 China 3. Department of Biological Sciences Tennessee State University Nashville TN 37209 USA 4. Department of Botany and Microbiology University of Oklahoma Norman OK 73019 USA

Temperature sensitivity of soil respiration (Q10) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q10 has high spatial heterogeneity. However, most biogeochemical models still use a constant Q10 in projecting future climate change and no spatial pattern of Q10 values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q10 in china at 8 km spatial resolution by assimilating data of soil organic carbon into a proc-ess-based terrestrial carbon model (CASA model). The results indicate that the optimized Q10 values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q10 values of different soil types range from 1.09 to 2.3., with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q10 is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q10 at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.

关键词： temperature sensitivity Q10 soil respiration global warming inverse analysis

Estimation of Sand Transportation Rate for Fixed and Semi-Fixed Dunes Using Meteorological Wind Data

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Pedosphere 2009年第1期19卷 129-136页

作者： HU Xia LIU Lian-You LI Shun-Jiang XIAO Bi-Lin LIU Mu-Xin Key Lab of Environment Change and Natural disaster Ministry of Education Beijing Normal Univeristy Beijing 100875 （China） academy of disaster {2. and {3. management Ministry of Civil Affairs/Ministry of Education Beijing Normal University Beijing 100875 （China） State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing 21008 （China） Institute of Plant Nutrition and Resources Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 （China） Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 （China）

Taibus County, Inner Mongolia, china, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2.00 was 57.3. kg cm-1 year-1 for the semi-fixed dunes and 4.56 kg cm-1 year-1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s-1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s-1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.

关键词： fixed and semi-fixed dunes meteorological wind data sand transportation rate wind erosion

A regression analysis of the effect of natural disaster on agriculture

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A regression analysis of the effect of natural disaster on a...