Jingbo Hu

Dr. Jingbo Hu


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 February 2025 in Remote Sensing
Verified
Journal Article
Open access
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JHJingbo Hu
Jingbo Hu
XDXin Du
Xin Du
QLQiangzi Li
Qiangzi Li
Yuan ZhangYuan Zhang
Yuan Zhang
HWHongyan Wang
Hongyan Wang
SGShuguang Gong
Shuguang Gong
The timely and precise estimation of crop aboveground biomass (AGB) is crucial for evaluating crop development and forecasting yields. The objective is to examine the differences, advantages, and limitations between time series parameters and single-time-phase indicators derived from various vegetation indices in AGB estimation. Moreover, we aim to quantitatively investigate and elucidate the impact of the topographic and geographic conditions of the study region on the estimation of highland barley AGB. Results indicate that AGB simulations utilizing time series parameters from vegetation index time series (VI-TS) curves yield satisfactory results for all three VIs, with the exception of the Normalized Difference Vegetation Index (NDVI), which encounters saturation issues. The performance metrics are as follows: the Enhanced Vegetation Index (EVI) (R2 = 0.73, RMSE = 20.24 g/m2), the Soil-Adjusted Vegetation Index (SAVI) (R2 = 0.67, RMSE = 20.97 g/m2), and the Normalized Difference Mountain Vegetation Index (NDMVI) (R2 = 0.54, RMSE = 24.92 g/m2). The inclusion of our quantitative terrain factor improves the simulation accuracies of NDVI, SAVI, and NDMVI. Overall, the terrain factor has a beneficial impact on the highland barley AGB simulation outcomes. This study establishes a foundational framework for the timely and precise estimation of highland barley biomass, crucial for monitoring agricultural production in plateau mountainous regions.