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Analyzing winter-wheat biochemical traits using hyperspectral remote sensing and deep learning
Accurate estimation of crop leaf and canopy biochemical traits, such as leaf dry matter
content (Cm), leaf equivalent water thickness (Cw), leaf area index (LAI), dry leaf biomass …
content (Cm), leaf equivalent water thickness (Cw), leaf area index (LAI), dry leaf biomass …
UAV and satellite synergies for map** grassland aboveground biomass in Hulunbuir Meadow Steppe
X Zhu, X Chen, L Ma, W Liu - Plants, 2024 - mdpi.com
Aboveground biomass (AGB) is an important indicator of the grassland ecosystem. It can be
used to evaluate the grassland productivity and carbon stock. Satellite remote sensing …
used to evaluate the grassland productivity and carbon stock. Satellite remote sensing …
Subfield-level crop yield map** without ground truth data: A scale transfer framework
Ongoing advances in satellite remote sensing data and machine learning methods have
enabled crop yield estimation at various spatial and temporal resolutions. While yield …
enabled crop yield estimation at various spatial and temporal resolutions. While yield …
Estimating crop leaf area index and chlorophyll content using a deep learning-based hyperspectral analysis method
The crop leaf area index (LAI) and leaf chlorophyll content (LCC) are essential indicators
that reflect crop growth status, and their accurate estimation is helpful for agricultural …
that reflect crop growth status, and their accurate estimation is helpful for agricultural …
A novel approach to estimate land surface temperature from landsat top-of-atmosphere reflective and emissive data using transfer-learning neural network
Abstract Land Surface Temperature (LST) is a crucial parameter in studies of urban heat
islands, climate change, evapotranspiration, hydrological cycles, and vegetation monitoring …
islands, climate change, evapotranspiration, hydrological cycles, and vegetation monitoring …
[HTML][HTML] Multi-decadal temporal reconstruction of Sentinel-3 OLCI-based vegetation products with multi-output Gaussian process regression
Operational Earth observation missions, like the Sentinel-3 (S3) satellites, aim to provide
imagery for long-term environmental assessment to monitor and analyze vegetation …
imagery for long-term environmental assessment to monitor and analyze vegetation …
Estimation of potato above-ground biomass based on the VGC-AGB model and deep learning
Accurate estimation of above-ground biomass (AGB) in potato plants is essential for effective
monitoring of potato growth and reliable yield prediction. Remote sensing technology has …
monitoring of potato growth and reliable yield prediction. Remote sensing technology has …
Near-surface air temperature estimation for areas with sparse observations based on transfer learning
Near-surface air temperature (NSAT) data is essential for climate analysis and applied
research in areas with sparse ground-based observations. In recent years, machine learning …
research in areas with sparse ground-based observations. In recent years, machine learning …
Canopy structure dynamics constraints and time sequence alignment for improving retrieval of rice leaf area index from multi-temporal Sentinel-1 imagery
Y Liu, B Wang, J Tao, S Tian, Q Sheng, J Li… - … and Electronics in …, 2024 - Elsevier
Due to the limited availability of in-situ observation data, most existing leaf area index (LAI)
inversion models do not fully leverage temporal information. Furthermore, the phenological …
inversion models do not fully leverage temporal information. Furthermore, the phenological …
[HTML][HTML] Transfer learning reconstructs submarine topography for global mid-ocean ridges
Mid-ocean ridges are unique, tectonically active geographical units on Earth that profoundly
control the ocean environment and dynamics at the global scale. However, high-resolution …
control the ocean environment and dynamics at the global scale. However, high-resolution …