ABI Development: Forest3D - an open source platform for lidar applications in forestry
ABI 开发:Forest3D - 林业激光雷达应用的开源平台
基本信息
- 批准号:1356077
- 负责人:
- 金额:$ 26.59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-09-01 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The University of California Merced is awarded a grant to develop an integrated software platform for LiDAR data analysis in forest research. Light Detection and Ranging (LiDAR) is an active remote sensing technology that measures the properties of scattered light to find the range of a distant object. Due to its ability to generate 3-dimensional (3D) data with high spatial resolution and accuracy, LiDAR technology is increasingly being used to obtain individual tree properties, measure forest biophysical parameters, and reconstruct virtual forests. Despite the increasing availability of LiDAR data, however, there are few platforms that allow forestry managers to fully explore this rich 3D data and seamlessly extract forest parameters. The platform provides the following functionality: data management and visualization, point cloud filtering, digital model generation, forest metrics calculation, regression analysis, individual tree segmentation, forest biophysical parameter extraction, and forest visualization. The platform will enable forestry managers to easily manipulate LiDAR data and extract a range of forest parameters of interest.The broader impacts of this research are threefold. First, it will help forest managers to better manage our precious natural resources and make more informed conservation decisions. Second, the platform will enable ecosystem scientists more broadly to extract 3D vegetation structure parameters from the LiDAR data, and thus advance the understanding of ecosystem patterns and processes. Third, this project will support education and research at the University of California, Merced which is a Hispanic Serving Institution. The PIs will actively train and recruit underrepresented students, and promote the use of LiDAR technology and spatial thinking in decision making processes for the local community, state, and federal agencies.
加州大学默塞德获得一笔赠款,用于开发森林研究中LiDAR数据分析的集成软件平台。光检测和测距(LiDAR)是一种主动遥感技术,可测量散射光的特性以找到远处物体的范围。由于其能够生成具有高空间分辨率和准确性的三维(3D)数据,LiDAR技术越来越多地用于获取个体树木属性,测量森林生物物理参数和重建虚拟森林。尽管LiDAR数据的可用性越来越高,但是,很少有平台允许林业管理人员充分探索这些丰富的3D数据并无缝提取森林参数。该平台提供以下功能:数据管理和可视化、点云过滤、数字模型生成、森林度量计算、回归分析、单木分割、森林生物物理参数提取和森林可视化。该平台将使林业管理人员能够轻松操作LiDAR数据并提取一系列感兴趣的森林参数。首先,它将帮助森林管理者更好地管理我们宝贵的自然资源,并做出更明智的保护决策。其次,该平台将使生态系统科学家能够更广泛地从LiDAR数据中提取3D植被结构参数,从而促进对生态系统模式和过程的理解。第三,该项目将支持加州大学默塞德的教育和研究,这是一个西班牙裔服务机构。PI将积极培训和招募代表性不足的学生,并促进当地社区,州和联邦机构在决策过程中使用LiDAR技术和空间思维。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Shawn Newsam其他文献
Metric Scaling for Dimensionality Reduction of Disordered Protein Dynamics
- DOI:
10.1016/j.bpj.2009.12.3456 - 发表时间:
2010-01-01 - 期刊:
- 影响因子:
- 作者:
Joshua L. Phillips;Edmond Y. Lau;V.V. Krishnan;Michael Rexach;Shawn Newsam;Michael E. Colvin - 通讯作者:
Michael E. Colvin
One-class remote sensing classification: one-class vs. binary classifiers
- DOI:
https://doi.org/10.1080/01431161.2017.1416697 - 发表时间:
2018 - 期刊:
- 影响因子:
- 作者:
Xueqing Deng;Wenkai Li;Xiaoping Liu;Qinghua Guo;Shawn Newsam - 通讯作者:
Shawn Newsam
Probing the Conformation Landscape of the Unfolded State: Do Disordered and Unfolded Dynamics Differ?
- DOI:
10.1016/j.bpj.2010.12.1227 - 发表时间:
2011-02-02 - 期刊:
- 影响因子:
- 作者:
Joshua L. Phillips;Edmond Y. Lau;Shawn Newsam;Michael E. Colvin - 通讯作者:
Michael E. Colvin
Shawn Newsam的其他文献
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{{ truncateString('Shawn Newsam', 18)}}的其他基金
EAGER: Exploratory Research on Deriving Flight Information from Drone Imagery for Safety Compliance
EAGER:从无人机图像中获取飞行信息以确保安全合规的探索性研究
- 批准号:
1747535 - 财政年份:2018
- 资助金额:
$ 26.59万 - 项目类别:
Standard Grant
ACM SIGSPATIAL Conference 2016: Student Activities and U.S.-Based Students Support
2016 年 ACM SIGSPATIAL 会议:学生活动和美国学生支持
- 批准号:
1644662 - 财政年份:2016
- 资助金额:
$ 26.59万 - 项目类别:
Standard Grant
CAREER: Social Multimedia as Volunteered Geographic Information: Crowdsourcing What-Is-Where on the Surface of the Earth Through Proximate Sensing
职业:社交多媒体作为自愿提供的地理信息:通过近距离感知众包地球表面的位置
- 批准号:
1150115 - 财政年份:2012
- 资助金额:
$ 26.59万 - 项目类别:
Continuing Grant
RUI: New Tools for Characterizing Protein Dynamics
RUI:表征蛋白质动力学的新工具
- 批准号:
0960480 - 财政年份:2010
- 资助金额:
$ 26.59万 - 项目类别:
Continuing Grant
III:Small:RUI:Integrating Image and Non-Image Geospatial Data
III:Small:RUI:集成图像和非图像地理空间数据
- 批准号:
0917069 - 财政年份:2009
- 资助金额:
$ 26.59万 - 项目类别:
Standard Grant
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