Hanlei Professor

Head of the Department of Land Engineering, Director of the Land Big Data Analysis Center of the Shaanxi Key Laboratory of Land Consolidation, Professor and PhD Supervisor. He has led more than 10 government-funded research projects, including General Program projects of the National Natural Science Foundation of China (NSFC), projects under the National Key R&D Program, and key fund and key R&D projects of Shaanxi Province; published more than 80 papers; published one monograph as editor-in-chief; and received the First Prize of the Natural Resources Science and Technology Award in 2024. He has also led multiple national-level education reform research projects, including New Engineering Research and Practice projects; led the completion and online launch of the Shaanxi-featured online course “Ecology”; guided students to win more than 20 awards in competitions at various levels; received the Grand Prize for Undergraduate Teaching Achievement at Chang'an University (ranked first); and has repeatedly been honored as an Outstanding Teacher, Outstanding Class Advisor, and Outstanding Graduation Thesis Supervisor at Chang'an University.

Research Areas:

Ecological Remote Sensing, Spatial Analysis and Modeling, Geographic Information System Development, Integrated Territorial Spatial Remediation and Ecological Restoration

Graduate Outcomes:

More than 30 master's and doctoral students have graduated. Their employment destinations include central and state-owned enterprises, where they work in areas such as spatiotemporal information platform development, Shan-Shui projects, and mine ecological restoration, as well as government agencies and public institutions, including research institutes and universities. Destinations for further study include Tongji University, Nanjing University, the University of Chinese Academy of Sciences, China Agricultural University, and other universities.

Undergraduate students who participated in the team's work and were admitted to graduate programs through recommendation have continued their studies at Zhejiang University, Wuhan University, Xi'an Jiaotong University, the University of Chinese Academy of Sciences, Northwest A&F University, Chang'an University, and other universities and research institutions.

Admissions and Programs:

We welcome researchers from all countries who are interested in Remote Sensing Science and Technology, Geographic Information Science, and Ecology to join our team!

Graduate admissions fields for master's and doctoral students: Land Engineering, Geography, and Resources and Environment. We welcome applications!

Associate Councillor of the World Association of Soil and Water Conservation (WASWAC)

Deputy Secretary-General, Land Use Engineering Professional Committee, Chinese Society of Agricultural Engineering

Member, Smart Farmland Use and Conservation Engineering Professional Committee, Chinese Society of Agricultural Engineering

Member, Youth Working Committee, Ecological Society of China

Executive Council Member and Deputy Secretary-General, Shaanxi Ecological Society

Executive Council Member, Shaanxi Geographical Society

Youth Editorial Board Member, Transactions of the Chinese Society of Agricultural Engineering and Science of Soil and Water Conservation

Project Review Expert for the National Natural Science Foundation of China, Shaanxi Provincial Department of Science and Technology, Shaanxi Provincial Department of Natural Resources, etc.

hanshuanglei@chd.edu.cn

The Land Ecological Engineering and Regional Environmental Modeling Team is led by a team leader and currently consists of one professor, one associate professor, and one senior engineer. The team's main research areas include ecological remote sensing, spatial analysis and modeling, geographic information system development, and integrated territorial spatial remediation and ecological restoration. The team operates more than 10 drones of various models, equipped with orthophoto, oblique, multispectral, hyperspectral, and thermal-infrared cameras. It has dedicated servers and comprehensive experimental facilities, and is fully capable of providing high-precision, multidimensional spatiotemporal raw data. The team has also established long-term field observation bases and welcomes exchanges and collaboration with universities, research institutions, and industry partners.

Main Research Areas:

1.  Inversion of Vegetation Parameters through Multi-Source Data Fusion

2.  Three-Dimensional Vegetation Structure and Ecosystem Functions

3.  Plant Functional Traits and Their Environmental Responses

4.  Remote Sensing of Biodiversity

5.  Sustainability and Resilience Assessment of Vegetation Restoration

6.  Terrain, Vegetation Patterns, and Soil Erosion

1.  Using an air–space–ground integrated approach, big data, and machine learning, information on terrain, vegetation structure, soil moisture, and other land-surface elements in the Loess Plateau was accurately extracted. Coordinated stability criteria for vegetation and soil moisture in arid and semi-arid regions were established. Digital ecosystem reconstruction methods were investigated by integrating multiple data sources, and the Dynamic Vegetation Monitoring Platform for the Northern Shaanxi Loess Plateau was developed by integrating remote-sensing image processing with spatial analysis of land-surface elements. This work provides important data support for the high-quality development of the Yellow River Basin.

2.  The mechanisms of soil erosion prevention and control were investigated in the slope–gully systems of the Loess Plateau, with a focus on differences in vegetation cover and spatial configuration on hillslopes. An automatic system for extracting and evaluating vegetation distribution at different slope positions was developed. This work provides a reference for optimizing the arrangement of soil and water conservation measures, reducing errors caused by relying solely on vegetation cover to estimate soil and water conservation benefits, and avoiding the misconception of pursuing vegetation coverage alone during vegetation establishment. It also provides an important scientific basis for the accurate evaluation of soil and water conservation benefits, the improvement of soil erosion equations, and the establishment and planning of artificial vegetation.

3.  Contaminated land was investigated through field surveys. The spatial distribution characteristics of heavy metals were analyzed, and the status of soil heavy-metal pollution was evaluated. A remote-sensing inversion model for soil heavy-metal pollution based on spectral analysis was established, and site-specific prevention, control, and remediation measures were proposed. This work provides scientific guidance for ecological protection, pollution management, and urban planning.

Lei Han.Intelligent Recognition System for Land-Surface Elements in the Loess Plateau (2025SR2068389)

Lei Han.GIS Software for Small-Watershed Delineation and Coding (2025SR1835595)

Lei Han.Deep Learning-Based Terrain Segmentation Software (2023SR0223527)

Lei Han, Huili Zhu, Zhao Liu, and Yonghua Zhao. Analysis of the Spatiotemporal Characteristics of Land Use/Land Cover and Hydrological Elements in Yan'an. Shaanxi Science and Technology Press, 2019.

2024 First Prize of the Natural Resources Science and Technology Award:Key Technologies and Applications for Intelligent Ecological and Environmental Monitoring through Multi-Source Remote-Sensing Collaboration

Professor and Doctoral Supervisor, School of Land Engineering, Chang'an University

Visiting Scholar, Faculty of Geo-Information Science and Earth Observation (ITC), 

University of Twente, Netherland