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UAV-HiRAP!
This is an open-source, web-based platform provides services for UAV flight route design and image analysis
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Services

主要包括:无人机航线规划、图像分析、中国沙地基础地理信息数据库和长期定位观测样地720度全景.

route_design

Route Design

给定样地顶点坐标和无人机飞行参数设置,生成满足拼图要求的最佳航线规划,并支持导出为litchi 飞控配置文件。

route_design

Image Analysis

基于决策树分类算法,通过提交满足要求的训练集,实现无人机影像像素的自动分类。

route_design

China Dryland Database

提供中国沙地基础地理信息数据库服务。

route_design

Site Panorama View

长期定位观测样地(内蒙古浑善达克沙地)720度全景图浏览功能。

News

  • publish

    2019.7.13

    课题组完成浑善达克大样地观测仪器安装与无人机观测

    7月13—16日,中国科学院地理科学与资源研究所段涛博士与乌日娜、韩东、姬婕、李晓雅、工程师共7人前往浑善达克沙地榆树疏林长期定位观测大样地调试涡度、荧光观测设备,同时开展了样地植被无人机观测。期间,大家与段涛博士交流了无人机影像处理过程中的疑难点,段博士结合研究经验提出了一些改进的建议。16日,王锋陪同中国林科院荒漠化所白建华书记及正蓝旗林业局朱景新局长共同了解了样地观测工作与植被恢复状况,随后考察了位于正蓝旗的乌和尔沁林场,探讨了将来建设浑善达克沙地榆树疏林长期定位观测研究站事宜。

  • publish

    2019.6.23

    课题组赴浑善达克大样地安装观测设备并完成无人机观测

    6月23日­—26日,乌日娜、李晓雅、韩东和仪器公司的工程师一行六人驱车至内蒙古正蓝旗浑善达克榆树疏林大样地进行无人机观测与实验仪器安装,顺利采集了样地影像数据、安装了荧光-通量-气象要素协同观测设备。

  • fig2

    2019.6.16

    硕士研究生韩东顺利完成学位论文答辩

    6月6日,硕士研究生韩东参加了林科院荒漠化所2016级硕士毕业答辩,他以“基于无人机和机器学习算法的榆树疏林草原植被动态研究”为题,报告了硕士研究生期间在浑善达克沙地榆树疏林草原大样地开展的研究工作,顺利通过答辩。



Our Team

See all team members in UAV-HiRAP Lab

WANG Feng

Project leader

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WANG Haozhou

Web designer

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JI Jie

Art designer

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UAV-HiRAP Lab is a research group under the Institute of Desertification Studies at Chinese Academy of Forestry (CAF-IDS). It is dedicated to applying latest technology such as artificial intelligence (AI) and unmanned aerial vehicles (UAV) in desertification management. We offer Masters, Ph.D and co-op opportunities and welcome any consultation.

Publications

Papers

  1. Haozhou Wang, Dong Han, Yue Mu, Lina Jiang, Xueling Yao, Yongfei Bai, Qi Lu, Feng Wang*. 2019. Landscape-level vegetation classification and fractional woody and herbaceous vegetation cover estimation over the dryland ecosystems by unmanned aerial vehicle platform. Agricultural and Forest Meteorology, 278: 107665 DOI: 10.1016/j.agrformet.2019.107665
  2. Feng Wang*, Xubin Pan, Cynthia Gerlein-Safdi, Cao Xiaoming, Wang Sen, Gu Lianhong, Wang Dongfang, Qi Lu*. 2019. Ecological restoration in Northern China: a contrasted picture. Land Degradation & development. DOI: 10.1002/ldr.3314
  3. 王锋*,卢琦. 2019. 沙地樟子松散生单木的天然更新幼苗空间分布模型. 林业科学.
  4. 吴隐,韩东,姚雪玲,张静,王锋*. 2019. 基于无人机高分辨率航空影像的榆树疏林空间分布格局及其地形效应. 热带地理. 39(4)
  5. Wu Rina, Cong Weiwei, LI Yonghua, LI Siyao, WANG Dongfang, Jia Zhiqing*, Wang Feng*. 2019. The Scientific Conceptual Framework for Ecological Quality of the Dryland Ecosystem: Concepts, Indicators, Monitoring and Assessment. Journal of Resources and Ecology, 10(2): 196-201.DOI: 10.5814/j.issn.1674-764x.2019.02.010
  6. Wang Shouqiang, Wang Junbang, Zhang Leiming, Xiao Zhishu, Wang Feng, Sun Nan, Li Daiqing, Chen Bin, Chen Jinghua, Li Yue, Wang Xiaobo, Wang Miaomiao. 2019 A National Key R&D Program: Technologies and and Guidelines for Monitoring Ecological Quality of terrestrial ecosystems in China. Journal of Resources and Ecology. 2019, 10(2): 105-111.
  7. 韩东,王浩舟,郑邦友,王锋*. 2018. 基于无人机和机器学习算法的榆树疏林草原植被分类和覆盖度动态估计.生态学报.38(18): 6655⁃ 6663
  8. Yue Mu, Feng Wang*, Bangyou Zheng, Wei Guo, Yiming Feng*. 2018. A rapid image-based method to determine the morphological characteristics of gravels on desert pavement. Geomorphology. 304, 89–98. DOI: 10.1016/j.geomorph.2017.12.027
  9. 穆悦,冯益明,高翔,韩东,吴隐,张谱. 2018. 基于无人机图像的戈壁表面砾石特征变化研究[J].林业科学研究, 31(2):55-62
  10. Feng Wang*. 2017. Artificial intelligence in research: UAV and artificial intelligence. Science. 357: 28-29. DOI: 10.1126/science.357.6346.28

Conference

  1. 王锋. 2018. 大数据在精准治沙工程评价、管理和政策中的应用与挑战. 三北工程精准治沙技术与管理培训班. 中国内蒙古阿拉善左旗。9月19日
  2. 韩东,王浩舟,王锋*. 2018. 基于无人机和机器学习算法的榆树疏林草原植被分类和覆盖度动态估计. 第17届中国生态学大会,生态遥感与应用分会. 中国南京,5月4-6日,(学术报告)
  3. Feng Wang. 2017. How to apply unmanned aerial vehicle and artificial intelligence to monitor ecological plots in dryland ecosystem. The workshop of monitoring techniques of observation stations in China Terrestrial Ecological Research Network. Nanning, China, 13-15 December. (Oral)
  4. Feng Wang. 2017. The study on vegetation and landforms classification coupled unmanned aerial vehicle and artificial intelligence. The Congress of China Physical Geography. Nanjing, China, 20-22 November. (Oral)
  5. Haozhou Wang, Feng Wang*, Xueling Yao, Yue Mu, Yongfei Bai*, Qi Lu*. 2017. UAV-HiRAP: A novel method to improve landscape-level vegetation classification and coverage fraction estimation with unmanned aerial vehicle platform. The 12th International Congress of Ecological (INTECOL). Beijing, China, August 21-25.(Oral).
  6. Wang Feng. 2016. Near-ground remote sensing of ecology and environment monitoring: application and perspective. Lecture. Chinese Agriculture University. Beijing, China, 16 December.(Oral)
  7. Mu Yue, Wang Feng*, Zheng Bangyou, Feng Yiming*. 2016. The gravel coverage and size of Gobi desert analyzed by a rapid image-based method[C]. IUFRO Regional Congress for Asia and Oceania 2016, Beijing, China, 24-27 October(Poster)
  8. Wu Yin, Zhang Jing, Yao Xueling, Guo Binbin, Wang Feng*. 2016. A novel spatially explicit model for sparse forest pattern based on digital terrain data. IUFRO Regional Congress for Asia and Oceania 2016, Beijing, China, 24-27 October.(Poster)
  9. Wang Feng. 2016. UAV: the application in the ecological monitoring. Lecture. Chinese Academy of Inspection and Quarantine. Beijing, China, 16 August.(oral)

Software copyrights

  1. 无人机高精度影像分析平台[简称: UAV-HiRAP] v3.0 2019. 软著登字第2019SR0286422
  2. 中国沙地基础地理信息数据平台[简称:GIP-DLC] v2.0 2018. 软著登字第2018SR921265
  3. 无人机高精度影像分析平台[简称: UAV-HiRAP] v2.0 2017. 软著登字第2017SR558256
  4. 无人机高精度影像分析平台[简称: UAV-HPIAP] v1.0 2016. 软著登字第2016SR198498
  5. 中国沙地基础地理信息web系统. 2016. 软著登字第2016SR036010