Unsupervised hyperspectral unmixing methods aim to extract endmember spectra and infer the proportion of each of these spectra in each observed pixel when considering linear mixtures. However, the interaction between sunlight and the Earth’s surface...
Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by v...
Hyperspectral imaging is a multidimensional optical technique with the potential of providing fast and accurate tissue classification. The main challenge is the adequate processing of the multidimensional information usually linked to long processing...
Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computin...
Solar-induced chlorophyll fluorescence (SIF) is closely related to plant photosynthetic activity and has been used in different studies as a proxy for vegetation health status. However, in order to use SIF as a relevant indicator of plant physiologic...
In push-broom hyperspectral imaging systems, the sensor rotation to the optical plane leads to linear spatial misregistration (LSM) in hyperspectral images (HSIs). To compensate for hardware defects through software, this paper develops four methods...
Inverting land cover reflectance or derived indices from low-spatial-resolution images to refine the spatial resolution of this data is cost-effective for land surface monitoring applications that face technical or budget limitations. Based on the li...
Spectral unmixing is a key process in identifying spectral signature of materials and quantifying their spatial distribution over an image. The linear model is expected to provide acceptable results when two assumptions are satisfied: (1) The mixing...
Two-photon microscopy enables monitoring cellular dynamics and communication in complex systems, within a genuine environment, such as living tissues and, even, living organisms. Particularly, its application to understand cellular interactions in th...
Hyperspectral unmixing, which decomposes mixed pixels into the endmembers and corresponding abundances, is an important image process for the further application of hyperspectral images (HSIs). Lately, the unmixing problem has been solved using deep...
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
As an invasive plant species, kudzu has been spreading rapidly in the Southeastern United States in recent years. Accurate mapping of kudzu is critical for effective invasion control and management. However, the remote detection of kudzu distribution...
Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as...
High-spectral-resolution hyperspectral data are acquired by sensors that gather images from hundreds of narrow and contiguous bands of the electromagnetic spectrum. These data offer unique opportunities for characterization and precise land surface r...
Sparse unmixing has been successfully applied in hyperspectral remote sensing imagery analysis based on a standard spectral library known in advance. This approach involves reformulating the traditional linear spectral unmixing problem by finding the...
Considering that ground areas with intense compositional variability appear as mixed pixels in hyperspectral data, we focus on the mixing problem imposed by the various volcanic products found in the vicinity of Mt. Etna’s volcanic craters. Mt. Etna,...
The goal of the paper is to detect pixels that contain targets of known spectra. The target can be present in a sub- or above pixel. Pixels without targets are classified as background pixels. Each pixel is treated via the content of its neighborhood...
Blind source separation (or unmixing) methods process a set of mixed signals, which are typically linear memoryless combinations of source signals, so as to estimate these unknown source signals and/or combination coefficients. These methods have bee...
The problem of mixed pixels negatively affects the delineation of accurate surface water in Landsat Imagery. Linear spectral unmixing has been demonstrated to be a powerful technique for extracting surface materials at a sub-pixel scale. Therefore, i...
Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember’s (pure pixel’s) distribution. This communication discusses inferring class fra...
Spatiotemporal fusion of remote sensing data is essential for generating high spatial and temporal resolution data by taking advantage of high spatial resolution and high temporal resolution imageries. At present, the Spatial and Temporal Adaptive Re...
The mangrove areas in Senegal have fluctuated considerably over the last few decades, and it is therefore important to monitor the evolution of forest cover in order to orient and optimise forestry policies. This study presents a method for mapping p...
Nighttime light remote sensing has aroused great popularity because of its advantage in estimating socioeconomic indicators and quantifying human activities in response to the changing world. Despite many advances that have been made in method develo...
We investigated a lab-based hyperspectral imaging system’s response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system’s performance. The spectral response to volumetr...
Hyperspectral technology has been used to identify pigments that adhere to the surfaces of polychrome artifacts. However, the colors are often produced by the mixing of pigments, which requires that the spectral characteristics of the pigment mixture...
A land-cover-based linear BRDF (bi-directional reflectance distribution function) unmixing (LLBU) algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI) reflectance with the moderate resolu...
Autofluorescent molecules are abundant in plant cells and spectral images offer means for analyzing their spectra, yielding information on their accumulation and function. Based on their fluorescence characteristics, an imaging approach using multiph...
For large areas, it is difficult to assess the spatial distribution and inter-annual variation of crop acreages through field surveys. Such information, however, is of great value for governments, land managers, planning authorities, commodity trader...
The goal of sparse linear hyperspectral unmixing is to determine a scanty subset of spectral signatures of materials contained in each mixed pixel and to estimate their fractional abundances. This turns into an...
The huge volume of hyperspectral imagery demands enormous computational resources, storage memory, and bandwidth between the sensor and the ground stations. Compressed sensing theory has great potential to reduce the enormous cost of hyperspectral im...
Organ-on-chips and scaffolds for tissue engineering are vital assay tools for pre-clinical testing and prediction of human response to drugs and toxins, while providing an ethical sound replacement for animal testing. A success criterion for these mo...
The advancement of hyperspectral remote sensing technology has enhanced the ability to assess and characterize land cover in complex ecosystems. In this study, a linear spectral unmixing algorithm was applied to NEON hyperspectral imagery in 2018 and...
Fractional green vegetation cover (FVC) is a useful parameter for many environmental and climate-related applications. A common approach for estimating FVC involves the linear unmixing of two spectral endmembers in a remote sensing image; bare soil a...
The assessment of changes in forest coverage is crucial for managing protected forest areas, particularly in the face of climate change. This study monitored forest cover dynamics in a 6535 ha mountain area located in north-west Romania as part of th...
Coastal ecosystems experience multiple anthropogenic and climate change pressures. To monitor the variability of the benthic habitats in shallow waters, the implementation of effective strategies is required to support coastal planning. In this conte...
Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This...
Organ-on-chips and scaffolds for tissue engineering are vital assay tools for pre-clinical testing and prediction of human response to drugs and toxins, while providing an ethically sound alternative to animal testing and a low-cost alternative to ex...
Visual image interpretation and digital image classification have been used to map and monitor mangrove extent and composition for decades. The presence of a high-spatial resolution hyperspectral sensor can potentially improve our ability to differen...
Hong Kong and Shenzhen have entirely different land-use development policies, resulting in a disparity in the increase rate of impervious surface area. Impervious surface estimation is a significant method for evaluating urbanization, so that countri...
As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity to accurately map large-scale urbanized areas for various science and policy applications. Although spectral mixture analysis (SMA) can provide spatia...
The finer resolution observation and monitoring of the global land cover (FROM-GLC) product makes it the first 30 m resolution global land cover product from which one can extract a global water mask. However, two major types of misclassification ex...
Compared to natural waters, mine waters represent an extreme water type that is frequently heavily polluted. Although they have been traditionally monitored by in situ measurements of point samples taken at regular intervals, the emergence of a new g...
The mineral-mapping capability of three spaceborne sensors with different spatial and spectral resolutions, the Environmental Mapping and Analysis Program (EnMap), Sentinel-2, and World View-3 (WV3), is assessed regarding bauxite mining wastes in Amp...
Climate change in the European Alps during recent years has led to decreased snow cover duration as well as increases in the frequency and intensity of summer heat waves. The risk of drought for alpine wetlands and temporary pools, which rely on wate...
Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd...
Hyperspectral analysis is a well-established technique that can be suitably implemented in several application fields, including materials science. This approach allows us to deal with data samples containing spatial and spectral information at very...
Dictionary pruning step is often employed prior to the sparse unmixing process to improve the performance of library aided unmixing. This paper presents a novel recursive PCA approach for dictionary pruning of linearly mixed hyperspectral data motiva...
The trade-off between spatial and temporal resolution limits the acquisition of dense time series of Landsat images, and limits the ability to properly monitor land surface dynamics in time. Spatiotemporal image fusion methods provide a cost-efficien...
Macrophages are important cells of the innate immune system that play many different roles in host defense, a fact that is reflected by their polarization into many distinct subtypes. Depending on their function and phenotype, macrophages can be gros...
Surface albedo is an important physical attribute of the climate system and satellite retrievals are useful for understanding how it varies in time and space. Surface albedo is sensitive to land cover and structure, which can vary considerably within...
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