Color Trends Research Articles

Determination of Color Preferences and Trend Colors in Hotel Room Interior Design

Buildings and environmental colors create differences in perception, both psychologically and physically. Colors interact with and have an impact on the form, space components, surroundings, materials textures, space lighting, the size of the surfaces, and the function and aesthetics of the space. Color preference varies according to personality traits, age and gender, habits and experiences, fashion, and style. The research is aimed to determine the color preferences and trends in hotel interior designs. Many hotel projects are designed and completed throughout the world every year. In this context, project designs awarded in international competitions were selected. To collect the data for the study, details of award-winning hotel interior designs available through competition websites are reviewed and the Adobe Color analytical tool is employed to characterize the color schemes reflected in the designs. Adobe Color is more successful than other tools in creating color schemes, such as the color wheel, gradient extraction, and theme extraction, suitable for all color selection methods, including colorful, bright, muted, deep, and dark options. As a result of this study, based on the designs awarded in 2022, it was determined that blue, red, and green colors were most frequently used, respectively. Furthermore, the data suggest that all colors were used in pastel tones, with light shades of blue mixed with different grays being used more frequently, while red and green generally were used in darker tones. The results were significantly correlated with the theoretical research and studies on user preferences.

A Study of the Comets with Large Perihelion Distances C/2019 L3 (ATLAS) and C/2019 O3 (Palomar)

This work analyzes the photometric data of the Oort spike comets C/2019 L3 (ATLAS) and C/2019 O3 (Palomar) obtained between 2016 and 2023 by the ATLAS network and the Belgian Olmen Observatory. The comets Palomar and ATLAS have a typical and unusually high activity level, respectively, based on the Afρ parameter corrected to phase angle zero at perihelion. The absolute magnitude of comets ATLAS and Palomar in the o-band is 4.71 ± 0.05 and 4.16 ± 0.02 respectively. The cometary activity of comets ATLAS and Palomar probably began at r > 13 au before perihelion and will end at r >14 au after perihelion, which means that they could remain active until the second half of 2026. The nucleus of comet ATLAS has a minimum radius of 7.9 km, and the nucleus of comet Palomar could be a little larger. The c − o colors of the comets ATLAS and Palomar are redder and bluer, respectively, at perihelion than the solar twin YBP 1194. These comets showed a bluish trend in the coma color with decreasing heliocentric distance. Comet Palomar probably had two outbursts after its perihelion, each releasing about 108 kg of dust. The slopes of the photometric profile of the comae of these comets were between 1 and 1.5, indicating a steady state during the observation campaign.

Application of DMSFNN-COA technique for brand image design

Color plays a pivotal role in product design, as it can evoke emotional responses from users. Understanding these emotional needs is crucial for effective brand image design. This paper introduces a novel approach, the Brand Image Design using Deep Multi-Scale Fusion Neural Network optimized with Cheetah Optimization Algorithm (BID-DMSFNN-COA), for classifying product color brand images as “Stylish” and “Natural”. By leveraging deep learning techniques and optimization algorithms, the proposed method aims to enhance brand image accuracy and address existing challenges in product color trend forecasting research. Initially, data are collected from the Mnist Data Set. The data are then supplied into the pre-processing section. In the pre-processing segment, it removes the noise and enhances the input image utilizing master slave adaptive notch filter. The Deep Multi-Scale Fusion Neural Network optimized with cheetah optimization algorithm effectively classifies the product colour brand image as “Stylish” and “Natural”. Implemented on the MATLAB platform, the BID-DMSFNN-COA technique achieves remarkable accuracy rates of 99 % for both “Natural” and “Stylish” classifications. In comparison, existing methods such as BID-GNN, BID-ANN, and BID-CNN yield lower accuracy rates ranging from 65 % to 85 % for “Stylish” and 65 %–70 % for “Natural” product color brand image design. The simulation outcomes reveal the superior performance of the BID-DMSFNN-COA technique across various metrics including accuracy, F-score, precision, recall, sensitivity, specificity, and ROC analysis. Notably, the proposed method consistently outperforms existing approaches, providing higher values across all evaluation criteria. These findings underscore the effectiveness of the BID-DMSFNN-COA technique in enhancing brand image design through accurate product color classification.

가정용 로봇청소기의 컬러 트렌드 분석

This study aims to analyze color trends focusing on household robot vacuum cleaners that have won Red Dot, iF, and IDEA design awards over the past four years. For this purpose, 89 products were selected from 2020 to 2023. The color analysis process involved collecting product photos and information posted on the Design Award website and extracting each product's primary, secondary, and accent colors. Munsell H V/C values were calculated by BabelColor CT&A based on sRGB data and distributed on the Hue & Tone color chart to conduct frequency analysis. At the same time, the frequency and characteristics by year were compared based on 18 color combination types. The results of the color trend synthesized were organized into color trends based on Hue and Tone charts, color trends for primary, secondary, and accent colors, and trends by color combination type.

Detection of an intranight optical hard lag with colour variability in blazar PKS 0735+178

ABSTRACT Blazars are a highly variable subclass of active galactic nuclei that have been observed to vary significantly during a single night. This intranight variability remains a debated phenomenon, with various mechanisms proposed to explain the behaviour including jet energy density evolution or system geometric changes. We present the results of an intranight optical monitoring campaign of four blazars: TXS 0506+056, OJ287, PKS 0735+178, and OJ248 using the Carlos Sánchez Telescope. We detect significant but colourless behaviour in OJ287 and both bluer- and redder-when-brighter colour trends in PKS 0735+178. Additionally, the g band shows a lag of $\sim 10\, \mathrm{min}$ with respect to the r, i, zs bands for PKS 0735+178 on 2023 January 17. This unexpected hard lag in PKS 0735+178 is not in accordance with the standard synchrotron shock cooling model (which would predict a soft lag) and instead suggests the variability may be a result of changes in the jet’s electron energy density distribution, with energy injection from Fermi acceleration processes into a post-shocked medium.

Pattern-based discrimination and visualization of metal ions through RGB coding of multicolor-emitting carbon dots

Herein, the single para-Phenylenediamine (PPD) source was used to synthesis three orange-, green-, and blue-emitting carbon dots (CDs) under different synthesis conditions. Due to the diverse fluorescence response of the synthesized CDs to heavy metal ions such as Au3+, Ag+, Cu2+, Fe3+, Hg2+, Cd2+, and Pb2+, a three-channel sensor array system for pattern-based discrimination and visualization of these metal ions was developed. The recorded fluorescence data was successfully classified into separate clusters without any overlapping through typical statistical methods such as principal component analysis (PCA) and hierarchical clustering analysis (HCA). We also introduced a new method of discrimination and determination by coding the fluorescence intensities of the three CDs into integer values from 0 to 255 and converting these values into a secondary color using the RGB additive mixing method to provide a single, unique, and visual fingerprint-like color for each metal ion. The colors obtained not only identified the selected metal ions and their binary and ternary mixed samples, but also provided a concentration-dependent trend of each specific color for metal ion quantification. Furthermore, the practicability of the constructed sensor array and the proposed RGB coding method was validated by the successful identification and quantification of unknown metal ions in real water samples.

Modeling fashion as an emergent collective behavior of bored individuals

Boredom is an aversive mental state that is typically evoked by monotony and drives individuals to seek novel information. Despite this effect on individual behavior, the consequences of boredom for collective behavior remain elusive. Here, we introduce an agent-based model of collective fashion behavior in which simplified agents interact randomly and repeatedly choose alternatives from a circular space of color variants. Agents are endowed with a memory of past experiences and a boredom parameter, promoting avoidance of monotony. Simulating collective color trends with this model captures aspects of real trends observed in fashion magazines. We manipulate the two parameters and observe that the boredom parameter is essential for perpetuating fashion dynamics in our model. Furthermore, highly bored agents lead future population trends, when acting coherently or being highly popular. Taken together, our study illustrates that highly bored individuals can guide collective dynamics of a population to continuously explore different variants of behavior.

A Prospective Study Demonstrating Early Prediction of Skin Toxicity From Radiation Therapy Using Radiomic Features From Optical and Infrared Images

Approximately 90% of patients undergoing breast cancer radiation therapyexperience skin toxicities that are difficult to classify and predict ahead of time. A prediction oftoxicityat the early stages of the treatment would provide clinicians with a prompt to intervene. The objectives of this study were to evaluate the correlation between skin toxicity and radiomic features extracted from optical and infrared (thermal) images of skin, and to develop a model for predicting a patient's skin response to radiation. Optical and infrared breast and chest-wall images were acquired daily during the course of radiation therapy, as well as weekly for 3 weeks after the end of treatment for 20 patients with breast cancer. Skin-toxicity assessments were conducted weekly until the patients' finalvisit. Skin color and temperature trends from histogram-based and texture-based radiomic features, extracted from the treatment area, were analyzed, reduced, and used in a cross-validation machine learning model to predict the patients' skin toxicity grades. A set of 9 independent color and temperature features with significant correlation to skin toxicitywere identified from 108 features. The cross-validation accuracy of a cubic Support Vector Machine remained >85% and area under the receiver operating characteristic curve remained>0.75,when reducing the input imaging data to include onlythe sessions with a biologically effective dosenot exceeding30 Gy(approximately the first third to first half of the total treatment dose). The quantitative analysis of radiomic featuresextracted from opticaland infrared (thermal) images of skinwas shown to be promising for predicting skin toxicities.

Postmortem Metabolism and Pork Quality Development Are Affected by Electrical Stimulation across Three Genetic Lines.

Variations in postmortem metabolism in muscle impact pork quality development. Curiously, some genetic lines are more refractile to adverse pork quality development than others and may regulate energy metabolism differently. The aim of this study was to challenge pork carcasses from different genetic populations with electrical stimulation (ES) to determine how postmortem metabolism varies with genetic line and explore control points that reside in glycolysis in dying muscle. Three genetic populations (GP) were subjected to ES (100 V or 200 V, 13 pulses, 2 s on/2 s off) at 15- or 25-min post-exsanguination, or no stimulation (NS). Genetic population affected relative muscle relative abundance of different myosin heavy chains, glycogen, G6P, and lactate concentrations. Genetic lines responded similarly to ES, but a comparison of ES treatment groups revealed a trend for an interaction between voltage, time of ES, and time postmortem. Higher voltage accelerated pH decline at 20 min up to 60 min postmortem. Trends in color and firmness scores and L* values were consistent with pH and metabolite data. These data show that genetic populations respond differently to postmortem perturbation by altering glycolytic flux and suggest differences in postmortem glycolysis may be partially responsible for differences in meat quality between genetic populations, though not entirely.

Conceptualizing the chromatic experience of environment: Two case studies using the Color Walk method

AbstractDesigning the colors of a new neighborhood without a color definition of facades is challenging task. While there is a wealth of research on color perception and architectural color design, tools and methods are needed to understand the chromatic experience of areas. Thus, this case‐study research aims to explore the chromatic experience by introducing a new ethnographic Color Walk method. The participants are professionals in the fields of architecture and color. Two voice‐recorded and transcribed discussions are examined from two perspectives: the suitability of the Color Walk to conceptualize the chromatic experience of neighborhoods and analyzing the main concepts used by professional participants. The analysis shows that the seven main concepts are: (1) material; (2) light; (3) views in/from/into the area; (4) atmosphere; (5) identity; (6) landscape/nature/landscape architecture; and (7) architecture. Architecture includes four subareas: (a) the color scale of the building design, (b) the color scale of the urban design, (c) the history of architecture, and (d) color trends. The results indicate that the Color Walk method allows conceptualizing how environmental colors are experienced. However, several repetitions are needed to confirm all the concepts. Furthermore, complex facade colors are only one element of the chromatic experience. Thus, other aspects should also be emphasized in environmental color design. The results also show that environmental color design is related to urban design and building design. The findings of this study contribute to existing research by expanding the concepts of urban design to environmental color design.

팬톤(Pantone) 컬러트렌드와 질감 테크닉을 활용한 헤어 커트 디자인 연구

In a pluralistic modern society, new trends have continuously emerged due to visual effects from diverse media. In addition, as individual personality becomes more important, people would express their identity with their own color. In addition, diverse programs with which a person’s personality and image can be guessed through color have been developed. As people’s interest in color continues, global Pantone color trends have had a significant influence on design industry. Under these circumstances, this study attempted to broaden the range of art expression by applying Pantone color trends to hairstyling and expand technical expressions, using texture. For this, to analyze color trends 2023 and propose haircut designs using texture techniques, first, the concept and characteristics of Pantone colors were analyzed. Second, the concept of haircut and texture techniques were investigated. Third, based on the above data, 3 different haircut designs were created, using Pantone colors and texture techniques. The study results confirm that it is possible to create unique designs by applying Pantone’s color trends to haircut. It is anticipated that there would be further studies which can make a contribution to the development of hair design by utilizing annual Pantone color trends.

Study on CAT activity of tomato leaf cells under salt stress based on microhyperspectral imaging and transfer learning algorithm

Salt stress easily leads to oxidative stress and promotes the catalase (CAT) response in tomato leaves. For the changes in catalase activity in leaf subcells, there is a need for a visual in situ detection method and mechanism analysis. This paper, taking catalase in leaf subcells under salt stress as the starting point, describes the use of microscopic hyperspectral imaging technology to dynamically detect and study catalase activity from a microscopic perspective, and lay the theoretical foundation for exploring the detection limit of catalase activity under salt stress. In this study, a total of 298 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. With the increase in salt solution concentration and the advancement of the growth period, the CAT activity value increased. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining CAT activity. The characteristic wavelength was extracted by five methods (SPA, IVISSA, IRFJ, GAPLSR and CARS), and four models (PLSR, PCR, CNN and LSSVM) were established according to the characteristic wavelengths. The results show that the random sampling (RS) method was better for the selection samples of the correction set and prediction set. Raw wavelengths are optimized as the pretreatment method. The partial least-squares regression model based on the IRFJ method is the best, and the coefficient of correlation (Rp) and root mean square error of the prediction set (RMSEP) are 0.81 and 58.03 U/g, respectively. According to the ratio of microarea area to the area of the macroscopic tomato leaf slice, the Rp and RMSEP of the prediction model for the detection of microarea cells are 0.71 and 23.00 U/g, respectively. Finally, the optimal model was used for quantitative visualization analysis of CAT activity in tomato leaves, and the distribution of CAT activity was consistent with its color trend. The results show that it is feasible to detect the CAT activity in tomato leaves by microhyperspectral imaging combined with stoichiometry.

How Eyes and Brain See Color: Definition of Color, Literature Review with Bibliometric Analysis, and Inquiry Learning Strategy for Teaching Color Changes to Student with Mild Intelligence Barriers

The study aims to investigate how the eyes and brain see color. We added information regarding the definition of color and a literature review regarding current theories and research trends in color, including how light comes to an object and its reflection onto the eyes and brain, making the brain interpret the object. Also, we considered the concept and the implementation of inquiry learning strategies in learning activities to recognize color changes from primary, secondary, to tertiary color. To support our study, we employed bibliometric analysis, helping us to find out the current studies in implementing inquiry learning strategies, specifically in recognizing color and its changes in education. The concept of color changes was delivered to children with mild intellectual disabilities. The results showed that the teaching concept of how eyes and brain see color as well as learning activities to recognize color changes for children with mild intellectual disabilities is still rare. Learning activities can be implemented if the learning process is carried out appropriately, confirmed by the learning outcomes. This study can provide information for researchers and educators in carrying out learning activities to recognize color changes in children with intellectual disabilities through inquiry learning strategies.

2023 S/S 팬톤 컬러 트렌드를 활용한 네일아트 색채 표현 디자인 연구

Color accounts for the largest portion in visual stimulation from outside, and it is a very powerful way of self-expression. Pantone forecasts color trends and announces ‘Color of the Year’ annually. In addition, the internationally influential American color institute suggests new color every season. This study attempted to diversify nail art images by visualizing color images and provide useful information with nail art which is influenced by trends. For this, fashion and makeup data according to the images of 10 signature colors from 2023 S/S Pantone Color were analyzed, and 10 nail art designs were created. Then, the results found the followings: First, after analyzing 10 different 2023 S/S Pantone Trend Colors, images, fashion, makeup and nail art were applied. Second, color tones were adjusted, using diverse drawing techniques while the background was expressed with a graduation technique. Then, feelings were emphasized, using lines. Third, unique nail art works were completed, using diverse objets, films and others. The above results confirm that there should be diverse studies on unique expression methods and continued R&Ds on nail trends in connection with more diverse fields with a goal of understanding 2023 S/S trend colors and developing nail art, a new creative genre. It is anticipated that the study results would be available as basic data for the above objectives.

Shifts, Trends, and Drivers of Lake Color Across China Since the 1980s

AbstractLakes are sentinels of global changes and integrators of processes in watersheds. Changes of lake water quality can be observed in shifts in lake color, however, the prevalence of shifts and trends in color and relevant factors remain elusive. Here, a comprehensive examination of color in 2,550 Chinese lakes from 1984 to 2021 revealed that color in 68% of the lakes shifted toward shorter visual wavelengths. Lakes in the Tibetan Plateau had larger declines in wavelength than lakes in other areas. The factors associated with reduced visual wavelengths varied in different ecoregions. A warmer and wetter climate in deep lakes in western China is associated with shifts toward blue. Increased vegetation in watershed and decreased wind are associated with green‐yellow shifting to green‐cyan color in shallow lakes of eastern China. Our study highlights the heterogeneous controls of climate and humans on changing patterns of lake colors.

Quasi-simultaneous photometric, polarimetric, and spectral observations of distant comet C/2014 B1 (Schwartz)

Context. We analyze the results of our comprehensive observations of the high-perihelion comet C/2014 B1 (Schwartz) with stable disk-shaped coma and jets in order to study its nature. Aims. The main objective of our study is to obtain new observational results for a unique disk-like comet C/2014 B1 (Schwartz) with a perihelion distance of 9.56 au. Methods. Quasi-simultaneous long-slit spectra, as well as photometric and polarimetric images with g-sdss and r-sdss filters, were acquired with the 6 m telescope of the Special Astrophysical Observatory on 2017 January 23. The BVR-band photometry of the comet was also performed at the 2m telescope of the Peak Terskol Observatory on 2017 January 31. We modeled the dynamics of the jets and the behavior of the color and polarization in the coma considering the dust as aggregated large particles. Results. We did not reveal any emissions in the spectra. The positions of two jets oriented along the position angles of 179° and 350° and the disk-like shape of the coma have remained unchanged for more than 4 yr. The most realistic model able to explain jets of such stable orientation includes the existence of two active sources located near the north and south poles of the rotating nucleus whose diameter was determined to be between 7.6 and 12.2 km depending on the albedo, of namely between 0.1 and 0.04, respectively. The high activity of the comet is characterized by the high dust production Afρ which varied from 4440 to 3357 cm between 2017 January 23 and 31. A significant difference between the radial surface brightness profiles of the jets and the ambient (undisturbed by the jets) coma is found. The color of the jet structures is much redder than that of the ambient coma, and the nucleus has a very red color, V − R=0.93m±0.19m. There are spatial variations of the color and polarization over the coma and jets. Conclusions. The observed trends in color and polarization, as well as the brightness profiles, can be explained by the fragmentation of aggregated particles formed by CO2/H2O ices, silicates, and organics, which are of ~1 mm in radius near the nucleus and ~10 μm in radius at the periphery of the coma.

Debris disk color with the Hubble Space Telescope

Context. Multiwavelength scattered light imaging of debris disks may inform dust properties including typical size and mineral composition. Existing studies have investigated a small set of individual systems across a variety of imaging instruments and filters, calling for uniform comparison studies to systematically investigate dust properties. Aims. We obtain the surface brightness of dust particles in debris disks by post-processing coronagraphic imaging observations, and compare the multiwavelength reflectance of dust. For a sample of resolved debris disks, we perform a systematic analysis on the reflectance properties of their birth rings. Methods. We reduced the visible and near-infrared images of 23 debris disk systems hosted by A through M stars using two coron-agraphs on board the Hubble Space Telescope: the STIS instrument observations centered at 0.58 µm, and the NICMOS instrument at 1.12 µm or 1.60 µm. For proper recovery of debris disks, we used classical reference differential imaging for STIS, and adopted non-negative matrix factorization with forward modeling for NICMOS. By dividing disk signals by stellar signals to take into account intrinsic stellar color effects, we systematically obtained and compared the reflectance of debris birth rings at ≈90º scattering angle. Results. Debris birth rings typically exhibit a blue color at ≈90º scattering angle. As the stellar luminosity increases, the color tends to be more neutral. A likely L-shaped color–albedo distribution indicates a clustering of scatterer properties. Conclusions. The observed color trend correlates with the expected blow-out size of dust particles. The color-albedo clustering likely suggests different populations of dust in these systems. More detailed radiative transfer models with realistic dust morphology will contribute to explaining the observed color and color–albedo distribution of debris systems.

The Value of Social Media Data in Fashion Forecasting

Problem definition: How to use social media to predict style color and jeans fit sales for a retailer. Academic/practical relevance: Neither retail practice nor the academic literature provides a method for using social media to predict style color and jeans fit sales for a retailer. We present and validate a systematic approach for doing that. Methodology: Demand forecasting in the fashion industry is challenging due to short product lifetimes, long manufacturing lead times, and constant innovation of fashion products. We investigate the value of social media information for color trends and jeans fit forecasting. We partner with three multinational retailers, two apparel and one footwear, and combine their proprietary data sets with web-crawled publicly available data on Twitter and the Google Search Volume Index. We implement a variety of machine learning models to develop forecasts that can be used in setting the initial shipment quantity for an item, arguably the most important decision for fashion retailers. Results: Our findings show that fine-grained social media information has significant predictive power in forecasting color and fit demands months in advance of the sales season, and therefore greatly helps in making the initial shipment quantity decision. The predictive power of including social media features, measured by the improvement of the out-of-sample mean absolute deviation over current practice ranges from 24% to 57%. Managerial implications: To our knowledge, this study is the first to explore and demonstrate the value of social media information in fashion demand forecasting in a way that is practical and operable for fashion retailers. With consistent results across all three retailers, we demonstrate the robustness of our findings over market and geographic heterogeneity, and different forecast horizons. Moreover, we discuss potential mechanisms that might be driving this significant predictive power. Our results suggest that changes in fashion demand are driven more by “bottom-up” changes in consumer preferences than by “top-down” influence from the fashion industry. Funding: This work was supported by Wharton School Fishman-Davidson Center for Service and Operations Management, the Wharton School Baker Retailing Center, and the Wharton School Risk Management Center Russell Ackoff Doctoral Student Fellowship. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1193 .

Quality attributes of different marinated oven-grilled pork neck meat

ABSTRACT Whereas herbs/spices serve as natural preservatives, and thermal processing makes animal meat products edible, combining them should complement each other. Additionally, the application of oven grilling to meat products continues to increase in popularity. However, there is a paucity of relevant published information specific to different marinated oven-grilled pork neck meat. Therefore, the quality attributes of different marinated oven-grilled pork neck meat were investigated, which involved chemical (pH, thiobarbituric acid reactive substance [TBARS], 2,2′-azinobis(3-ethylbenzothiaziline-6-sulfonate) [ABTS], 1,1-diphenyl-2-pierylhydrazy [DPPH], ferric reducing antioxidant power [FRAP]), physical (cooking weight loss, L*a*b* color, and textural cutting force), as well as organoleptic (sensory: flavor, appearance, tenderness, taste, and off-flavor; texture: hardness, chewiness, gumminess, graininess, and greasiness) aspects. In particular, the pork neck meat was procured from a porcine farm in Poland. Different marinated variants comprised constituent 0.5, 1, and 1.5% quantities of cranberry pomace (CP), grape pomace (GP), and Baikal skullcap (BS) that subsequently incorporated either African spice (AS) or industrial marinade/pickle (IM). Results showed decreases in ABTS, DPPH, FRAP, and TBARS in some marinated oven-grilled pork neck meat samples, alongside pH variations by difference that seemingly associated with increasing concentrations of either CP, BS, or GP, which might not always coincide with L*a*b* color trends as AS and IM were incorporated. Despite the many resemblances (p > .05), the sensory aspects fluctuated as textural chewiness, gumminess, and hardness increased in some samples, more evident when incorporating AS compared to IM. Overall, oven-grilling promises to moderate the range values of key quality attributes of different marinated pork neck meat samples in this study.

Temporal changes in the remote sensing reflectance at Lake Vänern

The Aerosol Robotic Network - Ocean Color (AERONET-OC) instrument located at the Pålgrunden site in Lake Vänern provides values of remote sensing spectral reflectance RRS(λ) since 2008. These in situ RRS(λ) indicated a temporal increase from 2015 at center-wavelengths in the green and red spectral regions. To investigate the environmental and climate processes responsible for this increase, water color trends in Lake Vänern were analyzed considering in situ limnological measurements, meteo-climatic quantities and additionally satellite-derived data products from the Moderate Resolution Imaging Spectroradiometer on board the Aqua platform (MODIS-A). Satellite ocean color RRS(λ) data assessed against in situ RRS(λ) from the Pålgrunden site showed satisfactory agreement at a number of spectral bands. Relying on these validation results, comprehensive statistical analysis were performed using MODIS-A RRS(λ). These indicated periodical changes between 2002 and 2021 with clear minima occurring between 2010 and 2013. The complementary analyses of temporal changes characterizing limological and meteo-climatic quantities, and also relationships between these quantities and RRS(λ), indicated the existence of complex and concurrent bio-geochemical processes influencing water color in Lake Vänern. In particular, significant correlations were observed between RRS(λ) and turbidity, and also between RRS(λ) and total biovolume. Additionally, an early warming of Lake Vänern surface waters was identified since spring 2014. This occurrence could potentially affect the vertical mixing and water exchange between turbid coastal and pelagic waters with implications for phytoplankton phenology.