Rong Shang - researchr alias

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Viewing Publication 1 - 10 from 10

2025

Improved estimation of the underestimated GEDI footprint LAI in dense forestsLijuan Liang, Rong Shang, Jing M. Chen, Mingzhu Xu, Hongda Zeng. gsis, 28(1):49-64, January 2025. [doi]

2023

2022

A 21-Year Time Series of Global Leaf Chlorophyll Content Maps From MODIS ImageryMingzhu Xu, Ronggao Liu, Jing M. Chen, Yang Liu 0120, Aleksandra Wolanin, Holly Croft, Liming He, Rong Shang, Weimin Ju, Yongguang Zhang, Yuhong He, Rong Wang. tgrs, 60:1-13, 2022. [doi]

2020

High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 dataWang Li, Zheng Niu, Rong Shang, Yuchu Qin, Li Wang, Hanyue Chen. aeog, 92:102163, 2020. [doi]

2019

Making Landsat Time Series Consistent: Evaluating and Improving Landsat Analysis Ready DataShi Qiu, Yukun Lin, Rong Shang, Junxue Zhang, Lei Ma 0005, Zhe Zhu. remotesensing, 11(1):51, 2019. [doi]

10, 122Rong Shang, Ronggao Liu, Mingzhu Xu, Yang Liu, Jadunandan Dash, Quansheng Ge. remotesensing, 11(8):939, 2019. [doi]

2018

Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth TrajectoriesRong Shang, Ronggao Liu, Mingzhu Xu, Yang Liu, Jadunandun Dash, Quansheng Ge. remotesensing, 10(1):122, 2018. [doi]

2016

Extracting the vegetation phenology of India monsoon forestRong Shang, Ronggao Liu, Yang Liu, Zuo Lu. igarss 2016: 1292-1295 [doi]

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