Mr. Xingwen Lin Profile

Xingwen Lin

at Institute of Remote Sensing and Digital Earth

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Publications (3)

Proceedings Article | 9 December 2015 Paper

Sensor intercomparison of distributed surface radiation measurement system

Baocheng Dou, Jianguang Wen, Xiuhong Li, Qiang Liu, Qing Xiao, Junhua Bai, Jingjing Peng, Xingwen Lin, Zhigang Zhang, Xiaodan Wu, Erli Cai, Jialin Zhang, Chongyan Chang

Proceedings Volume 9808, 98081F (2015) https://doi.org/10.1117/12.2207628

KEYWORDS: Sensors, Line width roughness, Remote sensing, Sensor networks, Distributed computing, Ultraviolet radiation, Infrared sensors, Spatial resolution, Data acquisition, Radiometry

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Proceedings Article | 9 December 2015 Paper

Preliminary validation of leaf area index sensor in Huailai

Erli Cai, Xiuhong Li, Qiang Liu, Baocheng Dou, Chongyan Chang, Hailin Niu, Xingwen Lin, Jialin Zhang

Proceedings Volume 9808, 98081C (2015) https://doi.org/10.1117/12.2207616

KEYWORDS: Digital photography, Photography, Sensors, Remote sensing, Vegetation, Cameras, Image processing, Image classification, Telecommunications

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Proceedings Article | 8 November 2014 Paper

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

Xingwen Lin, Jianguang Wen, Yong Tang, Mingguo Ma, Baocheng Dou, Xiaodan Wu, Lumin Meng

Proceedings Volume 9260, 926024 (2014) https://doi.org/10.1117/12.2069081

KEYWORDS: Remote sensing, Databases, Sensing systems, Sensors, Satellites, Standards development, Signal processing, Data storage, Product engineering, Sensor networks

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The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product validation.

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