Dengsheng Lu

Active 2002–2025

78
Papers
18,975
Citations
43
h-index
66
i10-index

Citations

Citations per year for Dengsheng Lu1973: 1 citations2003: 2 citations2004: 7 citations2005: 15 citations2006: 30 citations2007: 40 citations2008: 61 citations2009: 86 citations2010: 107 citations2011: 170 citations2012: 168 citations2013: 160 citations2014: 272 citations2015: 235 citations2016: 295 citations2017: 314 citations2018: 367 citations2019: 468 citations2020: 468 citations2021: 477 citations2022: 482 citations2023: 387 citations2024: 352 citations2025: 202 citations2026: 27 citations1974–2002: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 1,768 citing papers, 29.7% of this breakdownUnited States: 848 citing papers, 14.2% of this breakdownGermany: 228 citing papers, 3.8% of this breakdownUnited Kingdom: 216 citing papers, 3.6% of this breakdownIndia: 215 citing papers, 3.6% of this breakdownItaly: 209 citing papers, 3.5% of this breakdownAustralia: 177 citing papers, 3% of this breakdownCanada: 159 citing papers, 2.7% of this breakdownJapan: 142 citing papers, 2.4% of this breakdownSpain: 131 citing papers, 2.2% of this breakdownFrance: 129 citing papers, 2.2% of this breakdownBrazil: 124 citing papers, 2.1% of this breakdown
0%29.7%Other 27%

Fields

  • Environmental Science57.3%
  • Engineering25.2%
  • Computer Science8.9%
  • Earth and Planetary Sciences3%
  • Agricultural and Biological Sciences1.9%
  • Social Sciences1.2%
  • Other2.5%

Topics

  • Remote Sensing in Agriculture14.4%
  • Remote-Sensing Image Classification10.9%
  • Land Use and Ecosystem Services9.3%
  • Remote Sensing and Land Use8.4%
  • Remote Sensing and LiDAR Applications7.1%
  • Urban Heat Island Mitigation5.9%
  • Other44%

Coauthors

All papers

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  1. A survey of image classification methods and techniques for improving classification performance

    Authors: , - International Journal of Remote Sensing 2007 cited by 3,369

  2. Change detection techniques

    Authors: , , , - International Journal of Remote Sensing 2004 cited by 3,195

  3. A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

    Authors: , , , , , - International Journal of Digital Earth, Int. J. Digit. Earth 2014 cited by 842

  4. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies

    Authors: , , - Remote Sensing of Environment 2003 cited by 2,518

  5. The potential and challenge of remote sensing‐based biomass estimation

    Authors: - International Journal of Remote Sensing 2006 cited by 1,210

  6. Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

    Authors: , , , , , - Remote Sensing, Remote. Sens. 2016 cited by 248

  7. Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region

    Authors: , , , , , , - Remote Sensing, Remote. Sens. 2018 cited by 194

  8. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

    Authors: , , , , , , , - International Journal of Forestry Research 2012 cited by 286

  9. Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data

    Authors: , , , , - Remote Sensing, Remote. Sens. 2020 cited by 59

  10. Mapping croplands, cropping patterns, and crop types using MODIS time-series data

    Authors: , , , , , , , , , - International Journal of Applied Earth Observation and Geoinformation, Int. J. Appl. Earth Obs. Geoinformation 2018 cited by 195

  11. Forest aboveground biomass estimation in Zhejiang Province using the integration of Landsat TM and ALOS PALSAR data

    Authors: , , , , , , - International Journal of Applied Earth Observation and Geoinformation, Int. J. Appl. Earth Obs. Geoinformation 2016 cited by 145

  12. Use of impervious surface in urban land-use classification

    Authors: , - Remote Sensing of Environment 2006 cited by 659

  13. High-Resolution Urban Land Mapping in China from Sentinel 1A/2 Imagery Based on Google Earth Engine

    Authors: , , , , - Remote Sensing, Remote. Sens. 2019 cited by 122

  14. Exploring Bamboo Forest Aboveground Biomass Estimation Using Sentinel-2 Data

    Authors: , , , - Remote Sensing, Remote. Sens. 2018 cited by 78

  15. Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

    Authors: , , , , , , , - International Journal of Digital Earth, Int. J. Digit. Earth 2017 cited by 63

  16. Examining the Role of UAV Lidar Data in Improving Tree Volume Calculation Accuracy

    Authors: , , , , - Remote Sensing, Remote. Sens. 2022 cited by 37

  17. Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning

    Authors: , , , - Geo-spatial Information Science, Geo spatial Inf. Sci. 2024 cited by 20

  18. A comparative analysis of grid-based and object-based modeling approaches for poplar forest growing stock volume estimation in plain regions using airborne LiDAR data

    Authors: , , , - Geo-spatial Information Science, Geo spatial Inf. Sci. 2023 cited by 17

  19. Regional mapping of human settlements in southeastern China with multisensor remotely sensed data

    Authors: , , , - Remote Sensing of Environment 2008 cited by 332

  20. Cropland redistribution to marginal lands undermines environmental sustainability

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - National Science Review 2021 cited by 209

  21. Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data

    Authors: , , , - Remote Sensing, Remote. Sens. 2015 cited by 78

  22. Examining the Roles of Spectral, Spatial, and Topographic Features in Improving Land-Cover and Forest Classifications in a Subtropical Region

    Authors: , , , , , , - Remote Sensing, Remote. Sens. 2020 cited by 52

  23. Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon

    Authors: - International Journal of Remote Sensing 2005 cited by 422

  24. Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

    Authors: , - Acta Amazonica 2005 cited by 180