Results 81 to 90 of about 1,615,368 (250)
High Performance Computing for Hyperspectral Remote Sensing
Advances in sensor and computer technology are revolutionizing the way remotely sensed data is collected, managed and analyzed. In particular, many current and future applications of remote sensing in Earth science, space science, and soon in exploration science will require real- or near real-time processing capabilities.
Antonio Plaza +3 more
openaire +1 more source
High‐resolution visible‐light imagery from low‐altitude unmanned aerial vehicles, combined with superpixel segmentation and a Random Forest classifier, provides an efficient and scalable framework for mapping and monitoring crustose coralline algae and reef habitats.
Po‐Chien Lin +2 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
An object-based approach to quantity and quality assessment of heathland habitats in the framework of natura 2000 using hyperspectral airborne ahs images [PDF]
: Straightforward mapping of detailed heathland habitat patches and their quality using remote sensing is hampered by (1) the intrinsic property of a high heterogeneity in habitat species composition (i.e.
Spanhove, T. +9 more
core
A novel semi-fragile forensic watermarking scheme for remote sensing images [PDF]
Peer-reviewedA semi-fragile watermarking scheme for multiple band images is presented. We propose to embed a mark into remote sensing images applying a tree structured vector quantization approach to the pixel signatures, instead of processing each band ...
Serra Ruiz, Jordi +3 more
core +1 more source
We demonstrate that high‐resolution multispectral imagery combined with machine learning can accurately predict key biocrust functional indicators, particularly the UV‐protective pigment scytonemin, across dryland ecosystems. Using fine‐scale imagery acquired in the Chihuahuan Desert and Colorado Plateau, we identified spectral bands strongly ...
Raúl Román +8 more
wiley +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
Heathland ecosystems are currently in a degraded state due to agricultural transformations and the effects of climate change. They are semi‐natural ecosystems hosting a variety of species (fauna and flora), and they also carry landscape and cultural importance, hence the need to pay careful attention to their conservation.
J. Boissonnat, F. Binet, T. Houet
wiley +1 more source
AI‐Driven Circular Construction Waste Management for Advancing Sustainable Development
ABSTRACT Construction and demolition waste (C&DW) represents up to 40% of global solid waste, posing a significant barrier to achieving circular economy (CE) objectives and the Sustainable Development Goals (SDGs), particularly SDG 11 and SDG 12. However, construction waste management (CWM) systems remain constrained by fragmented data environments ...
Mohamed T. Elnabwy, Pablo Martinez
wiley +1 more source
Estimation of leaf area index from PROBA/CHRIS hyperspectral multi-angular data
Leaf Area Index (LAI) is a key structural and functional biophysical variable of the vegetated surfaces which is important in quantifying evapotranspiration rates and the energy exchange of terrestrial vegetation.
Luckman, A. +3 more
core +1 more source

