Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications

X Ma, X Zhu, Q Xie, J Jin, Y Zhou, Y Luo… - Global change …, 2022 - Wiley Online Library
Vegetation phenology has been viewed as the nature's calendar and an integrative indicator
of plant‐climate interactions. The correct representation of vegetation phenology is important …

Spring photosynthetic phenology of Chinese vegetation in response to climate change and its impact on net primary productivity

Y Xue, X Bai, C Zhao, Q Tan, Y Li, G Luo, L Wu… - Agricultural and Forest …, 2023 - Elsevier
In the context of global warming, the advancement of spring phenology in northern and
temperate regions due to increased temperatures has been widely reported. Early and …

[HTML][HTML] 3D-ResNet-BiLSTM Model: A Deep Learning Model for County-Level Soybean Yield Prediction with Time-Series Sentinel-1, Sentinel-2 Imagery, and Daymet …

M Fathi, R Shah-Hosseini, A Moghimi - Remote Sensing, 2023 - mdpi.com
Ensuring food security in precision agriculture requires early prediction of soybean yield at
various scales within the United States (US), ranging from international to local levels …

Magnitude and direction of green-up date in response to drought depend on background climate over Mongolian grassland

W Bai, H Wang, S Lin - Science of the Total Environment, 2023 - Elsevier
Increasing drought is one major consequence of ongoing global climate change and is
expected to cause significant changes in vegetation phenology, especially for naturally …

[HTML][HTML] Better representation of vegetation phenology improves estimations of annual gross primary productivity

H Gui, Q Xin, X Zhou, W Wu, Z Xiong - Ecological Informatics, 2024 - Elsevier
Carbon uptake by vegetation plays a vital role in the global carbon cycle. Annual gross
primary productivity (AGPP) represents the total amount of carbon compounds produced by …

Analysis of formal concepts for verification of pests and diseases of crops using machine learning methods

J Tussupov, M Yessenova, G Abdikerimova… - IEEE …, 2024 - ieeexplore.ieee.org
This article is devoted to a set of important areas of research: the analysis of formal
representations and verification of pests and pathogens affecting crops using spectral …

Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes

Q Wang, H Chen, F Xu, VA Bento, R Zhang, X Wu… - Scientific Reports, 2024 - nature.com
Previous studies have primarily focused on the influence of temperature and precipitation on
phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth …

Variations in phenology identification strategies across the Mongolian Plateau using multiple data sources and Methods

Z Li, Q Lai, Y Bao, X Liu, Q Na, Y Li - Remote Sensing, 2023 - mdpi.com
Satellite data and algorithms directly affect the accuracy of phenological estimation;
therefore, it is necessary to compare and verify existing phenological models to identify the …

Characterization and Evaluation of Global Solar-Induced Chlorophyll Fluorescence Products: Estimation of Gross Primary Productivity and Phenology

X Zheng, W Zhao, Z Zhu, Z Wang… - Journal of Remote …, 2024 - spj.science.org
As a proxy of vegetation photosynthesis, solar-induced chlorophyll fluorescence (SIF)
contains rich photosynthetic information that can reveal the physiological state of vegetation …

[HTML][HTML] Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature …

MS Islam, P Dash, AM Nur, H Ahmad, RM Panda… - Ecological …, 2024 - Elsevier
Abstract Chlorophyll-a (Chl-a) is a critical biological indicator of the eutrophic state of water
bodies, emphasizing the importance of its detailed characterization and continuous …