Results 61 to 70 of about 8,406 (209)
Monitoring forest recovery from disturbances at scale requires tracking tree dynamics, yet traditional ground‐based approaches are resource‐intensive. We present a pipeline to parameterize integral projection models (IPMs) using LiDAR data and hyperspectral‐based species maps to assess post‐fire recovery across large, forested areas at the Caribou ...
Jessica McLean +4 more
wiley +1 more source
Multiscale NMF based on intra-pixel and inter-pixel structure adjustment for spectral unmixing
Various improved nonnegative matrix factorization (NMF) methods have been widely used in spectral unmixing (SU), including nonlinear versions to counter for the lower spatial resolution and interaction between materials.
Tingting Yang +3 more
doaj +1 more source
Food requirements in the world have increased, evidencing the necessity to improve standard techniques of agricultural production. To do so, one option is through technological elements like hyperspectral remote sensing of vegetation and crops.
David Ruiz Hidalgo +2 more
doaj +1 more source
Imaging spectroscopy enables large‐scale biodiversity assessment, yet spectral diversity metrics are scale dependent. Across 15 NEON ecosystems, we find that spectral richness increases sub‐linearly from 3600 m2 to 4 km2, whereas spectral divergence shows weak or inconsistent scaling with area, underscoring the importance of scale‐aware interpretation ...
Meghan T. Hayden +8 more
wiley +1 more source
A Bridge Transformer Network With Deep Graph Convolution for Hyperspectral Image Classification
ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive memory and computational costs from calculating correlations between all tokens (especially as image size or spectral bands increase) and ...
Yuquan Gan +5 more
wiley +1 more source
MSFFNet: Multiscale Feature Fusion Network for Small Target Detection in Remote Sensing Images
ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although numerous algorithms have been developed for remote sensing image object detection, they still suffer from challenges such as low ...
Hui Zong +5 more
wiley +1 more source
Read the free Plain Language Summary for this article on the Journal blog. Abstract Emergent ecosystem properties, such as population and trait distributions, biodiversity and energy and water fluxes, occur because of the dynamic interactions of individuals in their environment.
Sarah J. Graves +8 more
wiley +1 more source
Hyperspectral proximal sensing was used to characterize the life stages and physiological responses of Diatraea saccharalis and to detect parasitism by Cotesia flavipes. Distinct spectral signatures differentiated eggs, larval instars, pupae, and adults, as well as live, dead, and parasitized larvae.
Souradji I. Bachirou +3 more
wiley +1 more source
Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation
ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu +4 more
wiley +1 more source
Evaluation of AVIRIS-NG hyperspectral images for mineral identification and mapping
Advancement of airborne hyperspectral remote sensing techniques provides subtle variations to identify minerals and to make distinctions between rock formations. These techniques clearly define barren land versus economically viable zones containing ores
Mahesh Kumar Tripathi, H. Govil
doaj +1 more source

