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Environmental Sciences

D-Index
45
Citations
8246
World Ranking
6372
National Ranking
643

Overview

Liangyun Liu is affiliated with the Chinese Academy of Sciences in China and has made substantial contributions to the field of environmental science, with a focus on remote sensing and land-use studies. Their research explores various aspects of global environmental changes, monitoring, and mapping using advanced remote sensing technologies and time-series satellite imagery.

Their recent noteworthy publications include:

  • "GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method," 2024, Earth system science data
  • "GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery," 2021, Earth system science data
  • "Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform," 2020, Earth system science data
  • "Finer-Resolution Mapping of Global Land Cover: Recent Developments, Consistency Analysis, and Prospects," 2021, Journal of Remote Sensing
  • "GISD30: global 30 m impervious-surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform," 2022, Earth system science data

The primary research topics covered by Liangyun Liu include:

  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics
  • Atmospheric and Environmental Gas Dynamics
  • Land Use and Ecosystem Services
  • Remote Sensing and Land Use
  • Remote Sensing and LiDAR Applications
  • Environmental Changes in China

Their publications predominantly appear in journals such as:

  • Zenodo (CERN European Organization for Nuclear Research)
  • Remote Sensing
  • Earth system science data
  • Journal of Remote Sensing
  • Remote Sensing of Environment

Liangyun Liu has frequently collaborated with several coauthors, including:

  • Xinjie Liu
  • Shanshan Du
  • Xidong Chen
  • Jidai Chen
  • Yuan Gao

Their work spans key subfields within environmental science, such as:

  • Global and Planetary Change
  • Ecology
  • Atmospheric Science
  • Environmental Engineering
  • Plant Science

Through the use of dense time-series satellite data and platforms like Google Earth Engine, Liangyun Liu's research addresses the dynamics of global land cover and impervious surfaces on a fine spatial scale. Their focus includes both methodological development and applied monitoring, providing datasets relevant for environmental assessment and planning.

Best Publications

  • GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery

    Xiao Zhang;Liangyun Liu;Xidong Chen;Yuan Gao;Yuan Gao

  • Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

    Wenjiang Huang;Wenjiang Huang;David W. Lamb;Zheng Niu;Yongjiang Zhang

  • Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform

    Xiao Zhang;Liangyun Liu;Changshan Wu;Xidong Chen

  • GISD30: global 30 m impervious-surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform

    Unknown

  • Directly estimating diurnal changes in GPP for C3 and C4 crops using far-red sun-induced chlorophyll fluorescence

    Liangyun Liu;Linlin Guan;Xinjie Liu

  • Finer-Resolution Mapping of Global Land Cover: Recent Developments, Consistency Analysis, and Prospects

    Liangyun Liu;Xiao Zhang;Yuan Gao;Xidong Chen

  • Downscaling of solar-induced chlorophyll fluorescence from canopy level to photosystem level using a random forest model

    Xinjie Liu;Luis Guanter;Liangyun Liu;Alexander Damm;Alexander Damm

  • Predicting grain protein content of winter wheat using remote sensing data based on nitrogen status and water stress

    Chunjiang Zhao;Liangyun Liu;Jihua Wang;Wenjiang Huang

  • Retrieval of global terrestrial solar-induced chlorophyll fluorescence from TanSat satellite

    Shanshan Du;Liangyun Liu;Xinjie Liu;Xiao Zhang

  • Prediction of grain protein content in winter wheat (Triticum aestivum L.) using plant pigment ratio (PPR).

    Z.J. Wang;Z.J. Wang;J.H. Wang;L.Y. Liu;W.J. Huang

  • Automatic Land-Cover Mapping using Landsat Time-Series Data based on Google Earth Engine

    Shuai Xie;Liangyun Liu;Xiao Zhang;Jiangning Yang

  • Predicting winter wheat condition, grain yield and protein content using multi‐temporal EnviSat‐ASAR and Landsat TM satellite images

    Liangyun Liu;Jihua Wang;Yansong Bao;Wenjiang Huang

  • Estimating winter wheat plant water content using red edge parameters

    Liangyun Liu;Jihua Wang;Wenjiang Huang;Chunjiang Zhao

  • The delineation of agricultural management zones with high resolution remotely sensed data

    Xiaoyu J. Song;Xiaoyu J. Song;Jihua Wang;Wenjiang Huang;Liangyun Liu

  • Detecting solar-induced chlorophyll fluorescence from field radiance spectra based on the Fraunhofer line principle

    Liangyun Liu;Yongjiang Zhang;Jihua Wang;Chunjiang Zhao

  • Consistency Analysis and Accuracy Assessment of Three Global 30-m Land-Cover Products over the European Union using the LUCAS Dataset

    Yuan Gao;Liangyun Liu;Xiao Zhang;Xidong Chen

  • Response of Canopy Solar-Induced Chlorophyll Fluorescence to the Absorbed Photosynthetically Active Radiation Absorbed by Chlorophyll

    Shanshan Du;Liangyun Liu;Xinjie Liu;Jiaochan Hu

  • Fine Land-Cover Mapping in China Using Landsat Datacube and an Operational SPECLib-Based Approach

    Xiao Zhang;Liangyun Liu;Xidong Chen;Shuai Xie

  • Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

    Dailiang Peng;Xiaoyang Zhang;Bing Zhang;Liangyun Liu

  • Measurement and Analysis of Bidirectional SIF Emissions in Wheat Canopies

    Liangyun Liu;Xinjie Liu;Zhihui Wang;Bing Zhang

  • Comparison of two methods of the fusion of remote sensing images with fidelity of spectral information

    Cunjun Li;Liangyun Liu;Jihua Wang;Chunjiang Zhao

  • Modelling paddy rice yield using MODIS data.

    Dailiang Peng;Jingfeng Huang;Cunjun Li;Liangyun Liu

  • Evaluating the potential of MODIS satellite data to track temporal dynamics of autumn phenology in a temperate mixed forest

    Lingling Liu;Lingling Liu;Liang Liang;Mark D. Schwartz;Alison Donnelly

  • Monitoring the seasonal bare soil areas in Beijing using multitemporal TM images

    Wanhui Chen;Liangyun Liu;Chao Zhang;Jihua Wang

Frequent Co-Authors

Wenjiang Huang
Wenjiang Huang Chinese Academy of Sciences
Bing Zhang
Bing Zhang Chinese Academy of Sciences
Yuan Gao
Yuan Gao Northeastern University
Alfredo Huete
Alfredo Huete University of Technology Sydney
Le Yu
Le Yu Tsinghua University
Xiaoyang Zhang
Xiaoyang Zhang South Dakota State University
Zheng Niu
Zheng Niu Chinese Academy of Sciences
Weimin Ju
Weimin Ju Nanjing University
Holly Croft
Holly Croft University of Sheffield

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