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Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review
Over the last few years, Deep learning (DL) approaches have been shown to outperform
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …
Monthly NDVI prediction using spatial autocorrelation and nonlocal attention networks
Accurate prediction of vegetation indices is useful for hel** maintain vegetation stability,
sustaining food production, and reducing socioeconomic losses. The traditional …
sustaining food production, and reducing socioeconomic losses. The traditional …
Trend Prediction of Vegetation and Drought by Informer Model Based on STL-EMD Decomposition of Ha Cai Tou Dang Water Source Area in the Maowusu Sandland
H Zheng, H Hou, R Li, C Tong - Agronomy, 2024 - mdpi.com
To accurately forecast the future development trend of vegetation in dry areas, it is crucial to
continuously monitor phenology, vegetation health indices, and vegetation drought indices …
continuously monitor phenology, vegetation health indices, and vegetation drought indices …
Mechanisms of climate change impacts on vegetation and prediction of changes on the Loess Plateau, China
Monitoring and forecasting the spatiotemporal dynamics of vegetation across the Loess
Plateau emerge as critical endeavors for environmental conservation, resource …
Plateau emerge as critical endeavors for environmental conservation, resource …
Next-level vegetation health index forecasting: A ConvLSTM study using MODIS Time Series
Abstract The Vegetation Health Index (VHI) is a metric used to assess the health and
condition of vegetation, based on satellite-derived data. It offers a comprehensive indicator …
condition of vegetation, based on satellite-derived data. It offers a comprehensive indicator …
Prediction of NDVI dynamics under different ecological water supplementation scenarios based on a long short-term memory network in the Zhalong Wetland, China
Wetland plants are a key factor in ecosystems but are threatened by water extraction and
water resource exploitation. Ecological water supplementation is a common solution to the …
water resource exploitation. Ecological water supplementation is a common solution to the …
Lightweight neural network for spatiotemporal filling of data gaps in sea surface temperature images
Optical remotely sensed data often have data gaps due to cloud coverage, which hinders
their full potential in many environmental applications. The question of how to accurately …
their full potential in many environmental applications. The question of how to accurately …
[HTML][HTML] How well can we predict vegetation growth through the coming growing season?
The prediction of vegetation growth under climate change has become much more important
in recent years, but is still a challenge. This study developed a machine learning method to …
in recent years, but is still a challenge. This study developed a machine learning method to …
Forecasting vegetation behavior based on planetscope time series data using RNN-based models
Accurate vegetation behavior forecasting is essential for understanding the dynamics of
plant life in the context of climate change and other natural or human-induced disturbances …
plant life in the context of climate change and other natural or human-induced disturbances …
[PDF][PDF] Forecasting localized weather impacts on vegetation as seen from space with meteo-guided video prediction
V Benson, C Requena Mesa, C Robin, L Alonso… - 2023 - pure.mpg.de
We present a novel approach for modeling vegetation response to weather in Europe as
measured by the Sentinel 2 satellite. Existing satellite imagery forecasting approaches focus …
measured by the Sentinel 2 satellite. Existing satellite imagery forecasting approaches focus …