Zobrazeno 1 - 10
of 4 453
pro vyhledávání: '"endmember"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-42 (2024)
Abstract Based on double-compressed sampling, a hyperspectral spectral unmixing algorithm (SU_DCS) is proposed, which could directly complete the endmember extraction and abundance estimation. On the basis of the linear mixed model (LMM), we designed
Externí odkaz:
https://doaj.org/article/cd9f68fea0994785a5e54725d0bd7f51
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104153- (2024)
Accurately estimating fractional cover of vegetated ecosystems over large areas is essential for many scientific studies, including climate change, land cover and land use, etc. Taking both accuracy and large spatial coverage into account, different
Externí odkaz:
https://doaj.org/article/cea8203d379644b6abb3eeeb6855a3ba
Publikováno v:
Geology, Ecology, and Landscapes, Vol 8, Iss 3, Pp 223-240 (2024)
Iron plays an important role in industrial and engineering fields development of a country and as such there is an enormous demand for iron in Ethiopia. However, a search for this valuable primary mineral resource exploration remains challenging and
Externí odkaz:
https://doaj.org/article/5664ca61bfa140149b3ed493bd466bf6
Autor:
Shah, Dharambhai a, Trivedi, Yogesh a, ⁎, Bhattacharya, Bimal b, Thakkar, Priyank a, Srivastava, Prashant c
Publikováno v:
In Advances in Space Research 1 January 2025 75(1):465-480
Akademický článek
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Akademický článek
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Autor:
John Waczak, David J. Lary
Publikováno v:
Remote Sensing, Vol 16, Iss 22, p 4316 (2024)
We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space of points sampled within a (n−1)-simplex
Externí odkaz:
https://doaj.org/article/a03a875274cc48c9899b696a1817fe24
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2531-2542 (2024)
Hyperspectral unmixing is to decompose the mixed pixel into the spectral signatures (endmembers) with their corresponding abundances. However, the ignorance of endmember variability in hyperspectral unmixing results in low performance. To solve this
Externí odkaz:
https://doaj.org/article/5e14d9baa3ec4eb29b6195369719ca3c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 732-747 (2024)
In recent years, the introduction of multiobjective evolutionary algorithms (MOEAs) into the field of endmember extraction (EE) in hyperspectral unmixing has demonstrated a breadth of results that surpass those derived from single-objective-based met
Externí odkaz:
https://doaj.org/article/189fa01bf36d4022bdb5197511da2ade
Autor:
Carl J. Legleiter, Tyler V. King
Publikováno v:
Journal of Open Research Software, Vol 12, Iss 1, Pp 13-13 (2024)
Remote sensing is often used to detect algae, but standard techniques do not provide information on the types of algae present or their potential to form a harmful algal bloom (HAB). We developed a framework for identifying algal genera based on refl
Externí odkaz:
https://doaj.org/article/e1124aa1802747aa8ab85bca7a633387