Overview

武汉大学空间要素激光探测实验室(Lidar-based Spatial Element Exploration and Detection Lab)是位于武汉大学测绘遥感信息工程国家重点实验室的科研机构,致力于探索激光技术在多学科领域的应用及相关研究。实验室成立于2019年,从地基差分吸收激光雷达的软硬件到星载差分吸收激光雷达的软件研发,一直处于国内领先水平。实验室由一支具有丰富经验和专业知识的科研团队组成,我们的目标是通过开展前沿研究来促进科学技术的发展和创新。

The Lidar-based Spatial Element Exploration and Detection Lab is a scientific research institution located in the State Key Laboratory of Information Engineering of Surveying, Mapping and Remote Sensing, Wuhan University, which is committed to exploring the application of laser technology in multidisciplinary fields and related research. The laboratory was established in 2019, and has always been at the leading level in China, from the software and hardware of ground-based differential absorption lidar to the software and research and development of spaceborne differential absorption lidar. The laboratory is composed of a scientific research team with extensive experience and expertise, and our goal is to promote the development and innovation of science and technology by conducting cutting-edge research.

Lab News

Research & Publication

Our current research projects include Atmospheric Imaging and Space Observations, Mechanism of interaction between laser and atmosphere . Check them all and you will find what you are looking for.

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Atmospheric Imaging and Space Observations

Atmospheric imaging research based on laser optics technology, including the distribution of clouds, aerosols and atmospheric pollutants, as well as remote sensing observations of the atmosphere using satellites and aircraft platforms.

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Carbon emissions from strong point sources

Through the research of laser remote sensing technology, the carbon emissions of strong point sources are monitored and evaluated, so as to provide accurate data support and provide decision-making basis for relevant departments to formulate emission reduction measures and management policies.

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Global CO2 monitoring

Differential absorption lidar technology is used to monitor CO2 concentration worldwide, and the temporal and spatial distribution of CO2 in the atmosphere is deeply studied, so as to provide important data for the study of global carbon cycle and climate change.

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Reception of global surface elevation

Optical remote sensing technology is used to study the acquisition and application of land surface elevation information, including the generation of digital elevation model (DEM), the extraction of topographic features, and the monitoring of land surface changes, so as to provide support for geological exploration, geomorphological research and natural disaster prevention.

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EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images

Geo-spatial Information Science
Yuan J, Ma X*, EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images, Geo-spatial Information Science, (2023) DOI: 10.1080/10095020.2023.2183145
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Retrieving CH 4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model

Atmospheric Chemistry and Physics
Shi T, Han Z, Han G, Ma X*,Chen H*, et al. Retrieving CH 4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model


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Research on lightweight disaster classification based on high-resolution remote sensing images

Remote Sensing
Yuan J, Ma X*, Han G, et al. Research on lightweight disaster classification based on high-resolution remote sensing images[J]. Remote Sensing, 2022, 14(11): 2577.
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The relationship between atmospheric boundary layer and temperature inversion layer and their aerosol capture capabilities

Atmospheric Research
Liu B, Ma X*, Ma Y, et al. The relationship between atmospheric boundary layer and temperature inversion layer and their aerosol capture capabilities[J]. Atmospheric Research, 2022, 271: 106121.
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Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data

Atmospheric Measurement Techniques
Li H, Liu B, Ma X*, et al. Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data[J]. Atmospheric Measurement Techniques, 2021, 14(9): 5977-5986.
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Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2. 5 over Wuhan, China

Remote Sensing
Ma X, Jiang W, Li H, et al. Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2. 5 over Wuhan, China[J]. Remote Sensing, 2021, 13(22): 4717.


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Study on collaborative emission reduction in green-house and pollutant gas due to COVID-19 lockdown in China

Remote Sensing
Zhang H, Ma X*, Han G, et al. Study on collaborative emission reduction in green-house and pollutant gas due to COVID-19 lockdown in China[J]. Remote Sensing, 2021, 13(17): 3492.



0

Book chapter

27

Paper

4

Phd Students

8

Master Students

Our Team

Principal Investigator


partners


Ma Xin (马昕)
Associate Professor (副教授)
maxinwhu@whu.edu.cn


Phd Students



Zhang Haowei (张豪伟)
haoweizhang@whu.edu.cn

Zhong Wanqin (钟琬溱)
wqzhong@whu.edu.cn

Yuan Jianye (袁建野)
yuan666@whu.edu.cn

Wang Lei (王磊)
wangsanshi@whu.edu.cn


Master Students



Yue Heng (岳恒)
hengyue@whu.edu.cn

Tong Zhe (童哲)
tongzhe@whu.edu.cn

Lyu Ruyin (吕如茵)
RuyinLyu@outlook.com


Zuo Chen (左晨)
2023206190053@whu.edu.cn

Su Xinyi (宿心一)
wyzsxy2012@163.com

Mo Wenyi (莫文一)
2019302120321@whu.edu.cn


Yan Haokai (闫皓凯)
haokaiyan@whu.edu.cn

Ouyang Qinxiang (欧阳钦翔)
2019302080217@whu.edu.cn

Gallery

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Phd Students Shi gives a speech in WHU

April,2023

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Associate Professor Ma received a birthday surprise in Lab

February,2023

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Graduation photo

June,2023

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Graduation photo

June,2023

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Field Experiment

Activity,2023

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Associate Professor Ma gives a speech in WHU

Activity,2023

Published

发表论文

1.Zhang H, Han G, Ma X*, et al. Spectral Energy Model-Driven Inversion of XCO 2 in IPDA Lidar Remote Sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 1-9.

2.Yuan J, Ma X*, Zhang Z, et al. EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images, Geo-spatial Information Science, (2023) DOI: 10.1080/10095020.2023.2183145

3.Shi T, Han Z, Han G, Ma X*,Chen H*, et al. Retrieving CH 4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model[J]. Atmospheric Chemistry and Physics, 2022, 22(20): 13881-13896.

4.Zuo C, Gong W, Gao Z, Ma X*,et al. Correlation analysis of CO2 concentration based on DMSP-OLS and NPP-VIIRS integrated data[J]. Remote Sensing, 2022, 14(17): 4181.

5.Yuan J, Ma X*, Han G, et al. Research on lightweight disaster classification based on high-resolution remote sensing images[J]. Remote Sensing, 2022, 14(11): 2577.

6.Liu B, Ma X*, Ma Y, et al. The relationship between atmospheric boundary layer and temperature inversion layer and their aerosol capture capabilities[J]. Atmospheric Research, 2022, 271: 106121.

7.马昕, 史天奇. 利用差分吸收激光雷达探测二氧化碳浓度廓线[J]. 武汉大学学报 (信息科学版), 2022, 47(3): 412-418.

8.Li H, Liu B, Ma X*, et al. Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data[J]. Atmospheric Measurement Techniques, 2021, 14(9): 5977-5986.

9.Ma X, Jiang W, Li H, et al. Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2. 5 over Wuhan, China[J]. Remote Sensing, 2021, 13(22): 4717.

10.Zhang H, Ma X*, Han G, et al. Study on collaborative emission reduction in green-house and pollutant gas due to COVID-19 lockdown in China[J]. Remote Sensing, 2021, 13(17): 3492.

11.Ma X, Zhang H, Han G, et al. A regional spatiotemporal downscaling method for CO 2 columns[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(10): 8084-8093.

12.Xu N, Ma X*, Ma Y, et al. Deriving highly accurate shallow water bathymetry from Sentinel-2 and ICESat-2 datasets by a multitemporal stacking method[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 6677-6685.

13.Xiang C, Ma X*, Zhang X, et al. Design of inversion procedure for the airborne CO 2-IPDA LIDAR: A preliminary study[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 11840-11852.

14.Shi T, Han Z, Gong W, Ma X*,et al. High-precision methodology for quantifying gas point source emission[J]. Journal of Cleaner Production, 2021, 320: 128672.

15.Ma X, Shi T, Xu H, et al. Noise reduction for ground-based atmospheric detection lidar: A universal method based on signal segmentation and reconstruction[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2021, 272: 107766.

部分主持项目
1 国家自然科学基金面上项目,基于差分吸收激光雷达的甲烷排放源监测方法研究。
2 国家自然科学基金青年基金项目,地基多波长激光雷达的温度自校正CO2廓线反演方法研究。
3 中央军委科学技术委员会XX特区,基于XX探测识别。
4 中央军委科学技术委员会XX特区,基于XX激光雷达的XX探测技术。

Contact Us

If you have some Questions or need Help! Please Contact Us!

I am always looking for prospective Postdoc, Ph.D. or M.S. students, interns and research assistants to work with.The applicant should have professional background in surveying and mapping, remote sensing, signal processing, computer, navigation and positioning. If you need to introduce yourself or ask about potential opportunities, please feel free to contact me.

For info about applying to our graduate program please see the link and the document. Please visit the our group webpage for details. In addition to working in my group at SPEED, you will also have the opportunity to interact with scientists at other organizations.