Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation
Frontiers in Plant ScienceSpectral analysis is a widely used method for monitoring photosynthetic capacity. However, vegetation indices-based linear regression exhibits insufficient utilization of spectral information, while full spectra-based traditional machine learning has ...
Xianzhi Deng +6 more
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An interactive tool for semi-automatic feature extraction of hyperspectral data
Open Geosciences, 2016 The spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass).
Kovács Zoltán, Szabó Szilárd
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American Journal of Botany, EarlyView.Abstract Interpretations of evolutionary outcomes are limited without incorporation of physiological ecology, and ecophysiological interpretations would benefit from incorporating evolutionary perspectives. Although there has been a rise of studies in the last 20 years between these fields, evolutionary studies that incorporate plant physiology have ...
Haley A. Branch
wiley +1 more source
Feasibility of estimating heavy metal contaminations in floodplain soils using laboratory-based hyperspectral data—A case study along Le’an River, China [PDF]
, 2011 Yaolin Liu +3 more
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Physically Based Predictive Modelling of Archaeological Proxies Using Cropmarks
Archaeological Prospection, EarlyView.ABSTRACT Cropmarks, as archaeological proxies, offer a valuable means of detecting buried sites through remote sensing. Yet, the scalability of such methods across varied archaeological contexts remains underexplored, and AI‐based modelling approaches are still in early stages.
Elias Gravanis, Athos Agapiou
wiley +1 more source
Archaeological Prospection, EarlyView.ABSTRACT Satellite remote sensing is among the most significant modern methodologies supporting field archaeology. In addition to its efficiency in identifying archaeological sites, remote sensing offers a safe and cost‐effective approach in conflict zones.
Amal Al Kassem +5 more
wiley +1 more source
Multisource Hyperspectral and LiDAR Data Fusion for Urban Land-Use Mapping based on a Modified Two-Branch Convolutional Neural Network [PDF]
, 2019 Quanlong Feng +3 more
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Cutting Through the Green: A Case for Grassland Archaeology Using UAV Multispectral Data
Archaeological Prospection, EarlyView.ABSTRACT Advances in low‐altitude remote sensing are needed to improve the effectiveness of archaeological prospection in the Netherlands. The geomorphological situation and land use history make applying various remote sensing and geophysical technologies particularly challenging.
Roeland Emaus
wiley +1 more source
How to Learn More? Exploring Kolmogorov–Arnold Networks for Hyperspectral Image Classification
Remote SensingConvolutional neural networks (CNNs) and vision transformers (ViTs) have shown excellent capability in complex hyperspectral image (HSI) classification.
Ali Jamali +4 more
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Generative AI, ESG Sensemaking, and Environmental Performance: an OIPT Perspective
Business Strategy and the Environment, EarlyView.ABSTRACT Despite growing enthusiasm for generative artificial intelligence (GenAI) in sustainability management, it remains unclear how such technologies translate vast ESG information into meaningful environmental outcomes. This study addresses this gap by investigating how ESG sensemaking capability mediates the relationship between GenAI integration
Surajit Bag +3 more
wiley +1 more source