Personal Information

Jing LI

Professor

Email： lijing@cumtb.edu.cn

Research Interests

Land Use and Land Information, Land Reclamation and Ecological Restoration, Remote Sensing on Environment, Sustainable Development of Resource-based Cities

Education/Work Background

1993.09-1997.07，Geography Department, Jilin Normal University, B.S.

1999.09-2002.07，Geography Department, Northeast Normal University, M.S.

2004.03-2008.04，Department of Surveying and Land Use, China University of Mining and Technology(Beijing), Ph.D.

1997.09-1999.07，Jilin Normal University, Assistant Professor

2002.03-2010.05，China University of Mining and Technology(Beijing), Assistant Professor/Lecturer

2010.06-2016.05，China University of Mining and Technology(Beijing), Associate Professor

2016.06- Present, Vice Director(2015-2018) and Head(2019-Present) of College of Geoscience and Surveying Engineering, China University of Mining and Technology(Beijing), Professor

Teaching Courses

Cartography, Land Reclamation and Ecological Restoration, Land Use Planning

Selected Research Funding as PI

[1] Remote Sensing Monitoring Method and Assessment of Forest Aboveground Carbon Storage in Coal Mining Area of the Middle Yellow River Basin. Ministry of Science and Technology of China, National Key R&D Program, Intergovernmental Science and Technology Innovation Cooperation (2022YFE0127700), 2023-2025,

[2]. Environment Monitoring and Green Ecological Restoration in Coal Mine Area. National Natural Science Foundation of China, National Natural Science Fund Project (No. 42142002), 2021-2022

[3]. Integrated Land Consolidation and Ecological Restoration in Liaocheng City. China Land Surveying and Planning Institute, 2020-2022

[4]. Ecological Change Process and Identification of Land Impact Boundaries in coal mining area. Ministry of Science and Technology of China, National Key R&D Program Sub-project (2016YFC0501101-4), 2016-2021

[5]. Land Space Development and Protection under the Context of Transformation in Resource-Exhausted Areas. Liaoning Urban and Rural Construction Planning and Design Institute, 2020-2022

[6]. Effects of Cultivated Land Changes in Coal and Grain Production Overlapped Areas by Ecosystem Service Functions Analysis. National Natural Science Foundation of China, Young Scientists Fund Project (No. 41501564), 2016-2018

[7]. Technology and Demonstration of Yellow River Sediment Filling Restoration in Large Coal Base Subsidence Areas. Ministry of Science and Technology of China, "Twelfth Five-Year" National Science and Technology Support Program Sub-project (2012BAC04B03), 2012-2015

[8]. Development and Demonstration of Ecological Reclamation Technology for Coal Mining Subsidence in Southwest Mountain Areas. Ministry of Land and Resources, Public Welfare Industry Scientific Research Special Project (No. 200911015-04), 2010-2013

Selected Publications

[1] Yan X, Li J*, Smith A R, et al. Evaluation of machine learning methods and multi-source remote sensing data combinations to construct forest above-ground biomass models. International Journal of Digital Earth. 2023, 16(2), 4471-4491.

[2] Yan X, Li J*, Yan X, et al. A method for quickly repairing the color difference of Landsat image bands. International Journal of Digital Earth. Spectroscopy and spectral analysis. 2023, 43(11), 3483-3491.

[3] Shao J, Li J*, Yan X, et al. Analysis of spatial and temporal variation characteristics and driving forces of NPP in Shanxi Province from 2000 to 2020 based on geodetector. Environmental Science. 2023, 44(01), 312-322.  

[4] Li J*, Liu Q, Liu P. Spatio-temporal variation and driving force analysis of vegetation coverage in Hulun Buir City from 1998 to 2018. Ecology. 2022, 42(01), 220-235.  

[5] Yan X, Li J, Yang D, et al. A Random Forest Algorithm for Landsat Image Chromatic Aberration Restoration Based on GEE Cloud Platform—A Case Study of Yucatán Peninsula, Mexico. Remote Sensing. 2022, 14(20), 5154.  

[6] Li J*, Jiang Z, Miao H, et al. Identification of cultivated land change trajectory and analysis of its process characteristics using time-series Landsat images: A study in the overlapping areas of crop and mineral production in Yanzhou City, China. Science of the Total Environment. 2022, 806, 150318.  

[7] Li J*, Yan X, Yan X, et al. Temporal and spatial variation characteristic of vegetation coverage in the Yellow River Basin based on GEE cloud platform. Journal of China Agricultural University. 2021, 46(05), 1439-1450.  

[8] Li J*, Liang J, Wu Y, et al. Quantitative Evaluation of Ecological Cumulative Effect in Mining Area Using a Pixel-based Time Series Model of Ecosystem Service Value. Ecological Indicators. 2021, 120.  

[9] Yan X, Li J*, Shao Y, et al. Driving forces of grassland vegetation changes in Chen Barag Banner, Inner Mongolia. GIScience & Remote Sensing.  2020, 57(6).

[10] Li J*, Yan X, Cao Z, et al. Identification of successional trajectory over 30 Years and evaluation of reclamation effect in coal waste dumps of surface coal mine. Journal of Cleaner Production. 2020, 269.

[11] Li J*, Deng X, Yang Z, et al. A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectralmages. Spectroscopy and Spectral Analysis. 2019, 39(12), 3788-3793.

[12] Li J*, Yang C, Yin S, et al. Evaluation and spatial distribution characteristics of soil heavy metals pollution in grassland open-pit coal mine area. Journal of China Coal Society. 2019, 44(12), 3676-3684.

[13] Yan X, Li J*, Yang Z. Dynamic remote sensing monitoring on the temporal-spatial changes of vegetation coverage in Chen Barag Banner from 2000 to 2016. Journal of China Agricultural University. 2018, 23(06), 121-129.

[14] Yan X, Li J, Yang Z. Analysis on temporal-spatial changes of vegetation cverrge in farming-pastoral ecotone of inner Mongolia. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018, 42, 2053-2057.

[15] Yang Z, Li J*, Carl E. Zipper, et al. Donovan. Identification of the disturbance and trajectory types in mining areas using multitemporal remote sensing images. Science of the Total Environment. 2018, 644, 916-927.

[16] Yang Z, Li J*, Yin S, et al. A method of identifying mining disturbance in arid or semi-arid steppe using inter-annual Landsat images-a case study in north-eastern China. Remote Sensing Letters. 2018, 9(12).

[17] Yang Z, Li J*, Shen Y, et al. A denoising method for inter-annual NDVI time series derived from Landsat images. International Journal of Remote Sensing. 2018, 39(12), 3816-3827.

[18]Adam J. Oliphant, R. H. Wynne, C. E. Zipper, W. M. Ford, P. F. Donovan, Jing Li. Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA. Biological Invasions, 2017, 19(1).

[19]Carl E. Z, Patricia F. D, Jess W. J, Jing L, Jennifer E. P, Roger E. S. Spatial and temporal relationships among watershed mining, water quality, and freshwater mussel status in and eastern USA river. Science of the Total Environment. 2016, 541: 603-615.

[20]Jing L, Carl E. Z, Patricia F. D, Randolph H. W, Adam J. O. Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery. Environmental Monitoring and Assessment, 2015, 187(9).