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Drainage Responses to the Activity of the Langshan Range-Front Fault and Tectonic Implications

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Journal of Earth Science 2018年第1期29卷 193-209页

作者： Shaopeng Dong Peizhen Zhang Huiping Zhang Wenjun Zheng Huixian Chen Key Laboratory of Active Tectonics and Volcano Institute of Geology China Earthquake Administration Beijing 100029 China State Key Laboratory of Earthquake Dynamics Institute of Geology China Earthquake Administration Beijing 100029 China School of Earth Science and Geological Engineering Sun Yan-Sen University Cruangzhou 510275 China map supervision center of sbsm Beijing 100830 China

Langshan, a monoclinic mountain, which started to uplift since Oligocene, bounds the northwest margin of the Hetao Basin. The continuous activity of the active normal Langshan range- front fault forms the typical basin-and-range landform in Langshan area and controls the landform evolution of Langshan. Langshan is an ideal place to study relationship between quantitative geomor- phological index and active deformation. According to study on knickpoints, fitting on longitudinal channel profiles and steepness index, we demonstrate that the main controlling factors on distribution of normalized steepness index of channels are not climate （precipitation）, lithology, sediment flux, but tectonic factor, or the activity of Langshan range-front fault. The short channels in southeast flank, whose lengths are shorter than 16 km, may be still in the non-steady status. If not considering these short channels, the distribution of normalized steepness index along the Langshan range-front fault appears like M-shape pattern, while the normalized steepness index in the middle section is higher than those at both ends. This pattern is well consistent with geometrical segmentation model of the Langshan range-front fault. Combining previous active tectonic research on Langshan range-front fault, which demonstrates the Langshan range-front fault has been in the stage of linkup, we reasonably infer the Langshan range-front fault now is the result of linkup of both fault which continuously bilaterally ex- tended independently. Our tectonic geomorphological study also supports the conclusion that the Langshan range-front fault has been in the stage of linkup. The formation of several knickpoints due to tectonic factor may have been caused by slip-rate variation because of linkup of both independent faults. Based on cognition above, we also proposed the geological and geomorphological evolutionary model of the Langshan range-front fault since Oligocene.

关键词： Langshan range-front fault Hetao Basin steepness index Langshan geomorphological evolutionary model.

The first geodetic investigation at the summit of Dome A,Antarctica

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Chinese Journal of Polar Science 2008年第1期19卷 85-92页

作者：张胜凯鄂栋臣李院生王泽民周春霞沈强 Chinese Antarctic center of Surveying and mapping SGGWuhan University Key Laboratory of Polar Surveying and mapping SBSM Polar Research Institute of China

Dome A is the highest ice feature in the Antarctica, up to now, little is known about surface topography at Dome A. The first Chinese ITASE expedition was carried out from Zhongshan station to Dome A during the 1996/1997 austral summer. During the 2004/2005 austral summer, the traverse was extended to the summit of Dome A which is 1228 km from Zhongshan Station by 21 st Chinese National Antarctic Research Expedition （CHINARE）. The real-time kinematic （RTK） GPS survey was carried out in the summit of Dome A during 2004/05 austral summer. The surface to-pography of Dome A was drawn up using the kinematic double-frequency GPS data covering an area of about 70 km^2. The accuracy of the kinematic survey is in the range of 0.20 m. Precise surface topography, bedrock morphology and internal laye- ring geometry are important for the future selection of the best site for deep drilling at Dome A.

关键词： Antarctica Dome A GPS topographic map.

Semantic Integration for Multi-Source Geo-Data based on Ontology——A Case of Integration of Chart and map

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Semantic Integration for Multi-Source Geo-Data based on Onto...

Design of Wireless Multi-media Sensor Network for Precision Agriculture

2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)

作者： WEN Min TANG Xin-ming SHI Shao-yu WEN Jian-qiang YAN Hao-wen Satellite Surveying and mapping Application center SBSM Beijing Chinese Academy of Surveying and mapping Lanzhou Jiaotong University Guangzhou Railway Group Corporation

To solve the problem of data-sharing between multi-source data for the reason of semantic heterogeneity, paper analysis the problem of semantic heterogeneity and propose a solution for it based on ontology, besides, paper take this solution to reality via VC++ 6.0 and have constructed the model of ontology by Protégé, completed the mapping table and the new coding system, to deal with the semantic gulf between chart and map, solution has been used in national 863-project.

关键词： ontology semantic integration chart map Protégé

来源： cnki会议评论

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China Communications 2013年第2期10卷 71-88页

作者：尹首一刘雷波周韧研孙忠富魏少军 Research center for Mobile Computing Tsinghua University Institute of Microelectronics Tsinghua University Chinese Academy of Agriculture Science

To satisfy the needs of modem pre-cision agriculture, a Precision Agriculture Sensing System （PASS） is designed, which is based on wireless multimedia sensor network. Both hardware and software of PASS are tai-lored for sensing in wide farmland without human supervision. A dedicated single-chip sensor node platform is designed specially for wireless multi-media sensor network. To guarantee the bulky data transmission, a bit-map index reliable data transmission mecha-nism is proposed. And a battery-array switch-ing system is design to power the sensor node to elongate the lifetime. The effectiveness and performance of PASS have been evaluated through comprehensive experiments and large-scale real-life deployment.

关键词： wireless sensor network low-power design reliable transmission pre-cision agriculture

RPNet: Rice plant counting after tillering stage based on plant attention and multiple supervision network

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作物学报:英文版 2023年第5期11卷 1586-1594页

作者： Xiaodong Bai Susong Gu Pichao Liu Aiping Yang Zhe Cai Jianjun Wang Jianguo Yao School of Computer Science and Technology Hainan UniversityHaikou 570228HainanChina Institute of Advanced Technology Nanjing University of Posts and TelecommunicationsNanjing 210003JiangsuChina Agricultural Meteorological center Jiangxi Meteorological BureauNanchang 330045JiangxiChina

Rice is a major food crop and is planted worldwide. Climatic deterioration, population growth, farmland shrinkage, and other factors have necessitated the application of cutting-edge technology to achieve accurate and efficient rice production. In this study, we mainly focus on the precise counting of rice plants in paddy field and design a novel deep learning network, RPNet, consisting of four modules: feature encoder, attention block, initial density map generator, and attention map generator. Additionally, we propose a novel loss function called RPloss. This loss function considers the magnitude relationship between different sub-loss functions and ensures the validity of the designed network. To verify the proposed method, we conducted experiments on our recently presented URC dataset, which is an unmanned aerial vehicle dataset that is quite challenged at counting rice plants. For experimental comparison, we chose some popular or recently proposed counting methods, namely MCNN, CSRNet, SANet, TasselNetV2, and FIDTM. In the experiment, the mean absolute error(MAE), root mean squared error(RMSE), relative MAE(rMAE) and relative RMSE(rRMSE) of the proposed RPNet were 8.3, 11.2, 1.2% and 1.6%, respectively,for the URC dataset. RPNet surpasses state-of-the-art methods in plant counting. To verify the universality of the proposed method, we conducted experiments on the well-know MTC and WED datasets. The final results on these datasets showed that our network achieved the best results compared with excellent previous approaches. The experiments showed that the proposed RPNet can be utilized to count rice plants in paddy fields and replace traditional methods.

关键词： Rice Precision agriculture Plant counting Deep learning Attention mechanism