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Doping and compositing are two universal design strategies used to engineer the electronic state of a material and mitigate its disadvantages. These two strategies are extensively applied to design efficient electrocatalysts for water splitting. Using cobalt oxide (CoO) as a model catalyst, it is proven that the oxygen evolution reaction (OER) performance can be progressively improved, first by Fe‐doping to form Fe‐CoO solid solution, and further by the addition of CeO2 to produce a Fe‐CoO/CeO2 composite. X‐ray absorption spectroscopy (XAS) reveals that distinct electronic interactions are induced by the processes of doping and compositing. Fe‐doping of CoO can break down the structural symmetry, changing the electronic structure of both Co and O species at the surface and decreasing the flat‐band potential (Vfb). In comparison, subsequent compositing of Fe‐CoO with CeO2 induces negligible electronic changes in the Fe‐CoO (as seen in ex situ characterizations), but significantly modifies the oxidative transformations of both Co and Fe under OER conditions. The spectroscopic investigations reveal that Fe‐doping and CeO2 compositing play different roles in modifying the electronic properties of CoO in its pristine state and during OER catalysis, in return, providing useful guidance for the design of more efficient electrocatalysts using these two strategies. [ABSTRACT FROM AUTHOR]

This study sought to improve pearl millet's nutritional, functional, and biochemical properties through malting and fermentation. Moringa oleifera leaf powder (MLP) was used as a fortificant. Mixture design was used to find optimal proportions for each component that yielded a high protein and or low saturated fat content. Twelve mixtures with varying ratios of fermented and malted pearl millet flour ranging between 30–65% and MLP between 5–15% were generated through I-Optimal mixture design. The mixtures were wet-cooked, freeze-dried, and analysed for protein and fat content. The data obtained were fitted to a linear mixture model, and the search for the optimum was conducted using Numerical Optimisation for maximising protein and minimising saturated fat. The linear model was suitable for explaining total protein and saturated fat variation with r2 of 0.50 and 0.51, respectively. Increasing MLP increased protein content. Two final formulations, Optimisation Solution 1 (OS1) and Optimisation Solution 2 (OS2), were generated through the optimisation process. Pearl millet's protein content increased by up to 22%, while saturated fat decreased by up to 13%; ash content increased by 75%. Polyphenol content and oxygen radical absorbance capacity increased by 80% and 25%, respectively. Final and peak viscosity were reduced by 90% and 95%, respectively. [ABSTRACT FROM AUTHOR]

Monsoon rain and its year-to-year variability have a profound influence on Africa's socio-economic structure by heavily impacting sectors such as agricultural and energy. This study focuses on major drivers of the east African monsoon during October-November-December (OND) which is the standard time window for the onset of the rainy season, be it unimodal or bimodal. Two drivers viz. Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) both separately indicate very strong positive connections with monsoon (OND) rain not only in the OND season with zero seasonal lag, but the signal is also present even taking IOD and ENSO a season ahead. A compositing approach is applied that can additionally identify strong signals when different combinations of ENSO and IOD phases act as confounding factors. Results of precipitation anomaly suggest that when IOD and ENSO are both on the same phase in July-August-September (JAS), a significant OND rainfall anomaly occurs around the east African sector: A deficit (excess) of OND monsoon rain occurs when both drivers are in a negative (positive) phase during JAS. A location Kibaha in Tanzania, for which station data are available, is considered for a more in-depth analysis. The uncertainty range in cumulative OND rainfall is also reduced to a large degree when IOD and ENSO phases are both negative in JAS. These results can be used for prediction purposes and interestingly, that criterion of IOD and ENSO being of same phase in JAS was again matched in 2022 (both negative) and hence it was possible to deliver early warnings for a deficit in rainfall a season ahead. Techniques to compute the monsoon onset as determined by meteorological services such as the Tanzania Meteorological Authority rely on various thresholds, which may also vary by country. To overcome some of the issues with thresholds-based techniques, other definitions of 'onset' take into account cumulative rainfall amount and such technique has also been tested and compared. In both approaches, late (early) onsets dominate in years when ENSO and IOD are both negative (positive) during JAS. In these cases, it is therefore possible to provide an estimation of cumulative rainfall and onset for OND in terms of average, median value, range and distribution of rainfall one season in advance. Such results have implications for optimizing agricultural, water and energy management, also mitigating possible severe production losses, which would impact the livelihoods of millions of Africans. [ABSTRACT FROM AUTHOR]

Pearl millet is an underutilised cereal. This study investigated the use of undervalued pearl millet grain in the manufacturing of value-added low sugar crackers that are protein-enhanced by the incorporation of Oyster mushroom. Equal amounts of pearl millet and wheat bread flour were mixed. This mixture was substituted to have 0 % (control), 5, 10 and 15 % Oyster mushroom powder. The moisture, protein, physical characteristics, in vitro starch digestibility of the composite flours and crackers were determined. The 15 % Oyster mushroom incorporation significantly increased the crackers’ protein (8.8 to 10.4 %). The inclusion of 15 % Oyster mushroom significantly reduced the in vitro starch digestibility at 20, 60, 120 min from 16 % to 13 %, 26 % to 23 and 37 % to 31 %, respectively. The 5 % Oyster mushroom incorporated cracker was the most liked (7.1 score on a 9-point hedonic scale). These easy to manufacture shelf-stable crackers, using low and affordable technology, from shelf-stable, low water activity flours can be used to alleviate protein malnutrition especially in the rural areas of developing nations where there is no electricity and refrigeration facilities.

We propose Factor Matting, an alternative formulation of the video matting problem in terms of counterfactual video synthesis that is better suited for re-composition tasks. The goal of factor matting is to separate the contents of a video into independent components, each representing a counterfactual version of the scene where the contents of other components have been removed. We show that factor matting maps well to a more general Bayesian framing of the matting problem that accounts for complex conditional interactions between layers. Based on this observation, we present a method for solving the factor matting problem that learns augmented patch-based appearance priors to produce useful decompositions even for video with complex cross-layer interactions like splashes, shadows, and reflections. Our method is trained per-video and does not require external training data or any knowledge about the 3D structure of the scene. Through extensive experiments, we show that it is able to produce useful decompositions of scenes with such complex interactions while performing competitively on classical matting tasks as well. We also demonstrate the benefits of our approach on a wide range of downstream video editing tasks. Our project website is at: https://factormatte.github.io/. [ABSTRACT FROM AUTHOR]

A key advantage of vector graphics over raster graphics is their editability. For example, linear gradients define a spatially varying color fill with a few intuitive parameters, which are ubiquitously supported in standard vector graphics formats and libraries. By layering regions filled with linear gradients, complex appearances can be created. We propose an automatic method to convert a raster image into layered regions of linear gradients. Given an input raster image segmented into regions, our approach decomposes the resulting regions into opaque and semi-transparent linear gradient fills. Our approach is fully automatic (e.g., users do not identify a background as in previous approaches) and exhaustively considers all possible decompositions that satisfy perceptual cues. Experiments on a variety of images demonstrate that our method is robust and effective. [ABSTRACT FROM AUTHOR]

The compositing modification strategy overcame the contradiction between the concentration and depth of photochromic centers and effectively enhanced the photochromic and luminescence modulation abilities of KSr 2 Nb 5 O 15 -based ceramics. However, the compositing concentration influences and potential competitive mechanism are unclear. In this work, the influences of Nb 2 O 5 composite concentration on the microstructures and the photochromic and luminescence modulation properties were systematically investigated. The overconcentration generated the aggregation of the second phase, which brought the competitive mechanism during the photochromic reaction and deteriorated the property. Moreover, to further strengthen the anti-counterfeiting ability, the textured composite ceramic was prepared by a template grain growth method. In addition to the grain-oriented microstructures and anisotropic optical properties, an atomic-scale explanation of the anisotropies of the defect distribution around interfaces was given. This work further explores the heterojunction modification mechanism and the atomic-scale origin of anisotropic photochromism and paves the way to develop and modify photochromic ceramics by interface design. [ABSTRACT FROM AUTHOR]

Remote sensing image composites are crucial for a wide range of remote sensing applications, such as multi-decadal time series analysis. The Advanced Very High Resolution Radiometer (AVHRR) instrument has provided daily data since the early 1980s at a spatial resolution of 1 km, allowing analyses of climate change-related environmental processes. For monitoring vegetation conditions, the Normalized Difference Vegetation Index (NDVI) is the most widely used metric. However, to actually enable such analyses, a consistent NDVI time series over the AVHRR time-span needs to be created. In this context, the aim of this study is to thoroughly assess the effect of different compositing procedures on AVHRR NDVI composites, as no standard procedure has been established. Thirteen different compositing methods have been implemented; daily, decadal, and monthly composites over Europe and Northern Africa have been calculated for the year 2007, and the resulting data sets have been thoroughly evaluated according to six criteria. The median approach was selected as the best-performing compositing algorithm considering all the investigated aspects. However, the combination of the NDVI value and viewing and illumination angles as the criteria for the best-pixel selection proved to be a promising approach, too. The generated NDVI time series, currently ranging from 1981–2018, shows a consistent behavior and close agreement to the standard MODIS NDVI product. The conducted analyses demonstrate the strong influence of compositing procedures on the resulting AVHRR NDVI composites. [ABSTRACT FROM AUTHOR]

Because of their rapid response, high sensitivity, and excellent thermal and chemical stabilities, photochromic ceramics have attracted great potential for optical applications in anti-counterfeiting and optical information storage. However, the inferior photochromic contrast restricted the further development of photochromic ceramics. Herein, a novel modification strategy for photochromic behavior is proposed in a KSr 2 Nb 5 O 15 -based system. A new heterojunction band structure was established at the interfaces in ceramics by compositing with transition metal oxides and generated novel transition paths for the excited carriers. After compositing with the Nb 2 O 5 second phase, the photochromic contrast △ R dec was almost doubled by additional color centers from the heterojunction structure. The related mechanism was confirmed by the photochromic behavior, thermoluminescence spectra and band structure features. Moreover, rapid, convenient and reversible laser bleaching behaviors was explored, and a more flexible anti-counterfeiting method was attempted through secondary laser adjustment of the photochromic pattern. This work aims to present a new modification viewpoint into photochromic ceramics by building a heterojunction structure. [ABSTRACT FROM AUTHOR]

This study sought to improve pearl millet’s nutritional, functional, and biochemical properties through malting and fermentation. Moringa oleifera leaf powder (MLP) was used as a fortificant. Mixture design was used to find optimal proportions for each component that yielded a high protein and or low saturated fat content. Twelve mixtures with varying ratios of fermented and malted pearl millet flour ranging between 30–65% and MLP between 5–15% were generated through I-Optimal mixture design. The mixtures were wet-cooked, freeze-dried, and analysed for protein and fat content. The data obtained were fitted to a linear mixture model, and the search for the optimum was conducted using Numerical Optimisation for maximising protein and minimising saturated fat. The linear model was suitable for explaining total protein and saturated fat variation with r2 of 0.50 and 0.51, respectively. Increasing MLP increased protein content. Two final formulations, Optimisation Solution 1 (OS1) and Optimisation Solution 2 (OS2), were generated through the optimisation process. Pearl millet’s protein content increased by up to 22%, while saturated fat decreased by up to 13%; ash content increased by 75%. Polyphenol content and oxygen radical absorbance capacity increased by 80% and 25%, respectively. Final and peak viscosity were reduced by 90% and 95%, respectively.

Semi-automatic, A.I.-specified stereographic scene processing is achieved by extending Blender with ChatGPT. We can generate objects and set scenes in Blender semi-automatically by invoking appropriate text prompts. Stereography techniques include anaglyphy, chromastereoscopy, and side-by-side display using binocular viewing. One can create a similar scene by copying and pasting the prompt used. It cannot always work identically, but it behaves roughly the same. First, we established Skybox and added scene Objects (Camera, Cube, etc.) in 3D view, materials, and animation with prompt. Stereographic images are created semiautomatically and compared across some qualities. The goal of this research is to validate those various stereographic techniques as rendered automatically in Blender.

Food waste is a rich organic matter that can potentially be converted into biogas as a source of renewable energy. The limitation in energy production lies in the presence of volatile fatty acid (VFA) during the anaerobic digestion of food waste due to the high degradation rate. The accumulation of VFA leads to a decrease in pH that exceeds the optimal pH range of 6.8–7.6 for methanogens, thus inhibiting methanogenesis and affecting biogas production. In the present study, a symbiotic culture of bacteria and yeast (SCOBY) and kombucha mixed inoculum and compost was applied as an alternative treatment method to alleviate inhibition. The digestion efficiency was evaluated on pH, total alkalinity (TA), total volatile fatty acid (TVFA), total solid (TS), and volatile solid (VS) throughout the digestion period of 80 days to analyse the stability of the system. The results revealed that SCOBY and kombucha mixed inoculum caused system instability, inducing inhibition at TVFA of 12,874.1 mg/L, while the pH dropped to 5.23. The inhibition in the digestion system with only the SCOBY inoculum occurred at TVFA of 11,908.3 mg/L, and the pH dropped to 5.67. The biogas and methane yield quantified from the mixed inoculum is 8.792E−4 L/L d, comparatively lower than the ethanol pre-fermentation treatment method. These findings indicate that the addition of compost improved the pH, VS, and TVFA. [ABSTRACT FROM AUTHOR]

The article explores the concept of studio filmmaking in the context of early Hollywood and a new incarnation of studio filmmaking in the age of digital visual effects. The author analyses the old studio era in terms of shaping the cinematic image (primarily compositing) and the meaning of the studio, understood as an atelier. Kalbarczyk argues that originally the final look of the film used to be achieved by blending all the shot elements in the physical space of the studio, while nowadays the final form is most often created in a virtual space, deepening the decentralization of the filmmaking process. The author argues that more than the atelier space, the new studio filmmaking concept would refer to the holistic way of thinking about cinema as a heterogeneous structure, not so much attained integrally through filming, but carefully constructed. Various dimensions of studio filmmaking are discussed using the following films: Sunrise: A Song of Two Humans (1927), Citizen Kane (1941), Everest (2015) and Avengers: Endgame (2019). [ABSTRACT FROM AUTHOR]

The paper deals with the production of large scale vegetation products derived from PROBA-V 100 m satellite images. Image compositing and mosaicking are needed to create seamless products on a global or continental scale. In the study, we have analysed and compared two compositing methods. Evaluation of the methods was focused on the visual inspection of the product seamlessness, and efficiency in eliminating (reducing) the influence of inadequate pixels that were misclassified by a cloud detection algorithm. During the compositing procedure, we also created a raster quality map and calculated statistical properties of the mosaics in order to assess the quality of the product.

Animation is a sequence of frames played per seconds and started to be a successful production, But the problems started when the animated films started asking about composing 2D animation with 3D animation , all these needs forced animation software to start to develop its options so that it can serve animation films and animators requirements starting by Adobe After effects which offers great results in motion graphics , animation and composting , but also Toon boom have released harmony premium The most powerful software ever created for animation production so that we can Access to a complete toolset for traditional frame-by-frame animation. Or Build simple to advanced cut out rigs with specialized tools. Master controllers save time when animating sophisticated rigs. Also we can Import 3D Objects as Once we have exported a model using a 3D authoring software, we can import it into a 2.5 Scene and integrate it to set up your 2D animation scene.we have the possibility to convert our 3D models to the *.fbx format compatible to be imported to Harmony. This will allow us to render 3D files with the associated textures without the need to copy over the textures manually .Using multiplane space is a 2.5 Animation where we can move layers forward and backward on the Z-axis. Latest Animation softwares like toonboom harmony brings us a true three-dimensional space where we can actually rotate your camera and layers on all axes. This lets us perform a 360 degree rotation around elements, create a floor and even build sets!Once we have a 3D set, the exciting part is to do a camera move in it. Once we know how to do this, we can enjoy the delights of working in 3D space and traveling inside with 2D or 3D animations together .we can change the near and far clipping planes of the camera. The near plane is the point on the camera cone where the camera is located. The far clipping plane is the far end of the camera cone. Nothing outside that range is visible. This is useful when dealing with 3D elements and 3D sets. And Finally these latest solutions helps us to Animate 3D models and their individual parts directly while integrating 3D elements with 2D characters.

We propose a novel system for portrait relighting and background replacement, which maintains high-frequency boundary details and accurately synthesizes the subject's appearance as lit by novel illumination, thereby producing realistic composite images for any desired scene. Our technique includes foreground estimation via alpha matting, relighting, and compositing. We demonstrate that each of these stages can be tackled in a sequential pipeline without the use of priors (e.g. known background or known illumination) and with no specialized acquisition techniques, using only a single RGB portrait image and a novel, target HDR lighting environment as inputs. We train our model using relit portraits of subjects captured in a light stage computational illumination system, which records multiple lighting conditions, high quality geometry, and accurate alpha mattes. To perform realistic relighting for compositing, we introduce a novel per-pixel lighting representation in a deep learning framework, which explicitly models the diffuse and the specular components of appearance, producing relit portraits with convincingly rendered non-Lambertian effects like specular highlights. Multiple experiments and comparisons show the effectiveness of the proposed approach when applied to in-the-wild images. [ABSTRACT FROM AUTHOR]

A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data.

We present a deep learning-based algorithm that can automatically rotoscope people in a given scene, without any user input. Current approaches to image matting require a significant amount of human input, irrespective of whether it is manually rotoscoped or through a chroma key. This study shows that this algorithm can perform as well as and even surpass the rotoscoping capabilities of the Adobe After Effects' RotoBrush tool, in a variety of scenes comprising different lighting conditions, movements, and subjects. This makes it suitable for integration within a visual effects (VFX) pipeline. [ABSTRACT FROM AUTHOR]

Copyright of Geodetic Courier / Geodetski Glasnik is the property of Union of Associations of Geodetic Professionals in Bosnia & Herzegovina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Image mosaicing is an effective means of constructing a single seamless image by aligning multiple partially overlapped images. Over the years, the research attention on mosaicing has increased a lot due to the growing applications and subsequently, many algorithms related to mosaicing and its contributing steps have come into existence. Though, the varied approaches for mosaic generation are effective, several difficulties arise in each step of mosaicing which need to be addressed specifically. The aim of this review is to provide an insight into the existing mosaicing algorithms, along with their merits and shortcomings. Additionally, the manuscript provides a classification of these algorithms based on their domain of processing, application, image type, and visual attributes. Furthermore, a comparison among various mosaicing methods is presented to find out which algorithm works best for a particular application and image type. Finally, the paper is concluded with a highlight on future research directions. • A comprehensive review of state-of-the-art mosaicing methods is presented. • A detailed classification of existing mosaicing techniques is introduced. • Comparative analysis is provided for easy selection of mosaicing algorithms for specific application. • Challenges of mosaicing are discussed and possible future directions are highlighted. [ABSTRACT FROM AUTHOR]

It is convinced that controllable preparation of active materials and electrode play a key role in improving the electrochemical performances. Herein, a modified hydrothermal technique focusing on assistance of counterpart through slow release feeding of metal ions is supplied by introducing a planar metal counterpart inner the hydrothermal chamber. The influence of slow release feeding rather than conventional batch-feeding of metal ions on targeted product in-situ grown on interested metal support is investigated through compositing, doping and/or possible induction effect. Moreover, anisotropic feeding of this counterpart mode supplies the possibility of oriented induction. As a result, components and morphologies, as well as structure or even crystalline are strongly depended on the counterpart kinds, or even its forms (net, foam or foil). In addition, as-prepared M x O y @M electrodes exhibit enhanced capacitance and cycling stability even with high mass loading, and their asymmetric supercapacitors also deliver good energy density and excellent cycling durability. This work supplies a new strategy in developing tuned electrodes. • A planar metal counterpart was added in the hydrothermal chamber. • An inner slow release strategy was introduced. • Cu-MoO 2 @Mo, MoO 2 @Mo, Ni-Fe 3 O 4 /Fe 3 S 4 @Fe, Co 3 O 4 /CoS/Ni(OH) 2 @Co. • Specific capacitance and cyclability were improved with increased loading amount. [ABSTRACT FROM AUTHOR]

Copyright of e-Journal of Science & Technology is the property of e-Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study is about an efficient synthesis of 360° video and 3D graphics. First, the video image filmed by a binocular integral type 360° camera was stitched, and location values of the camera and objects were extracted. And the data of extracted location values were moved to the 3D program to create 3D objects, and the methods for natural compositing was researched. As a result, as the method for natural compositing of 360° video image and 3D graphics, rendering factors and rendering method were derived. First, as for rendering factors, there were 3D objects’ location and quality of material, lighting and shadow. Second, as for rendering method, actual video based rendering method’s necessity was found. Providing the method for natural compositing of 360° video image and 3D graphics through this study process and results is expected to be helpful for research and production of 360° video image and VR video contents. [ABSTRACT FROM AUTHOR]

Abstract Many applications that target dynamic land surface processes require a temporal observation frequency that is not easily satisfied using data from a single optical sensor. Sentinel-2 and Landsat provide observations of similar nature and offer the opportunity to combine both data sources to increase time-series temporal frequency at high spatial resolution. Multi-sensor image compositing is one way for performing pixel-level data integration and has many advantages for processing frameworks, especially if analyses over larger areas are targeted. Our compositing approach is optimized for narrow temporal-intervals and allows the derivation of time-series of consistent reflectance composites that capture field level phenologies. We processed more than a year's worth of imagery acquired by Sentinel-2A MSI and Landsat-8 OLI as available from the NASA Harmonized Landsat-Sentinel dataset. We used all data acquired over Germany and integrated observations into composites for three defined temporal intervals (10-day, monthly and seasonal). Our processing approach includes generation of proxy values for OLI in the MSI red edge bands and temporal gap filling on the 10-day time-series. We then derive a national scale crop type and land cover map and compare our results to spatially explicit agricultural reference data available for three federal states and to the results of a recent agricultural census for the entire country. The resulting map successfully captures the crop type distribution across Germany at 30 m resolution and achieves 81% overall accuracy for 12 classes in three states for which reference data was available. The mapping performance for most classes was highest for the 10-day composites and many classes are discriminated with class specific accuracies >80%. For several crops, such as cereals, maize and rapeseed our mapped acreages compare very well with the official census data with average differences between mapped and census area of 11%, 2% and 3%, respectively. Other classes (grapevine and forest classes) perform slightly less well, likely, because the available reference data does not fully capture the variability of these classes across Germany. The inclusion of the red edge bands slightly improved overall accuracies in all cases and improved class specific accuracies for most crop classes. Similarly, our gap filling procedure led to improved mapping accuracies when compared to nongap-filled 10-day features. Overall, our results demonstrate the valuable potential of approaches that utilize data from Sentinel-2 and Landsat which allows for detailed assessments of agricultural and other land-uses over large areas. Highlights • Compositing approach for optimized synthesis over narrow temporal intervals • >14 months of Sentinel-2a and Landsat-8 data processed over Germany • Detailed and accurate national scale crop and land cover map derived for 2016 • 10-day interval outperforms monthly and seasonal composites for mapping • Mapped acreages for several classes compare well to agricultural census [ABSTRACT FROM AUTHOR]

Copyright of Megatrends & Media is the property of University of SS. Cyril & Methodius in Trnava, Faculty of Mass Media Communication and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We introduce an extremely scalable and efficient yet simple palette-based image decomposition algorithm. Given an RGB image and set of palette colors, our algorithm decomposes the image into a set of additive mixing layers, each of which corresponds to a palette color applied with varying weight. Our approach is based on the geometry of images in RGBXY-space. This new geometric approach is orders of magnitude more efficient than previous work and requires no numerical optimization. We provide an implementation of the algorithm in 48 lines of Python code. We demonstrate a real-time layer decomposition tool in which users can interactively edit the palette to adjust the layers. After preprocessing, our algorithm can decompose 6 MP images into layers in 20 milliseconds. [ABSTRACT FROM AUTHOR]

Remote sensing based monitoring of deforestation in the tropics is crucial to better understand global land use change and related changes in ecosystem service provision and to inform governments and civil society on the effectiveness their forest protection policies. In Brazil, deforestation has been closely coupled to the expansion of grazing and cropping systems primarily in the tropical forest, but no spatially explicit high resolution database on deforestation exists that captures tropical forest clearing prior to 2000. The open Landsat archive provides >45 years of imagery and is well suited for wall-to-wall assessments of historic deforestation dynamics which are valuable to policy development and environmental impact assessments. Image analysis procedures for reconstructing long-term deforestation dynamics over large areas need to cope with regions and time periods for which the archive contains heterogeneous data densities on a yearly and decadal basis. We create for the first time yearly 30 m maps of long term, annual deforestation dynamics (LTAD) covering the period from 1984 to 2014 for Pará and Mato Grosso, two Brazilian federal states that cover much of the Brazilian arc-of-deforestation. Our results provide valuable insights into historic deforestation trends, with annually increasing deforestation from 1990 to 1999 for both Pará and Mato Grosso. Peak deforestation occurred in 2004 after which deforestation leveled off – with a more pronounced decrease in Mato Grosso than in Pará. Contrary to Mato Grosso, Pará again experienced increasing annual forest clearing in recent years. For the time period after 2000, we provide an in-depth comparison with two widely used products, the Brazilian PRODES and the Global Forest Change maps (GFC, Hansen et al., 2013 ). Our deforestation estimates (407,000 ± 42,000 km 2 at 95% confidence level) are above those provided by PRODES, while GFC results are closer to our estimates for the comparison period. Recent PRODES estimates are consistently below our and the GFC results. Overall, our results exemplify the potential of open image archives for multi-decadal, wall-to-wall and fine grain reconstruction of forest change. The presented approach prototypes similar assessments of tropical forest dynamics globally faced with issues of data scarcity. [ABSTRACT FROM AUTHOR]

A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel-Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data. [ABSTRACT FROM AUTHOR]

Capturing high frequency water surface dynamics via optical remote sensing is important for understanding hydro-ecological processes over seasonally flooded wetlands. However, it is a difficult task due to the presence of clouds on satellite images. This study proposed the MODerate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) Minimum Value Composite (MinVC) algorithm to generate daily water surface data at a 250-m resolution. The algorithm selected pixelwise minimum values from the combined daily Terra and Aqua MODIS NDVI data within a 15-day moving window. Consisting mainly of cloud and water surface information, the MinVC NDVI data were segmented for water surfaces over the Poyang Lake, China (2000−2017) by using an edge detection model. The water surface mapping result was strongly correlated with the Landsat based result (R2 = 0.914, root mean square error, RMSE = 223.7 km2), the cloud free MODIS image based result (R2 = 0.824, RMSE = 356.7 km2), the recent Landsat-MODIS image fusion based result (R2 = 0.765, RMSE = 403 km2), and the hydrodynamic modeling result (R2 = 0.799). Compared to the equivalent eight-day MOD13 NDVI based on the Constraint View-Angle Maximum Value Composite (CV-MVC) algorithm, the daily MinVC NDVI highlighted water bodies by generating spatially homogenous water surface information. Consequently, the algorithm provided spatially and temporally continuous data for calculating water submersion times and trends in water surface area, which contribute to a better understanding of hydro-ecological processes over seasonally flooded wetlands. Within the framework of sensor intercalibration, the algorithm can be extended to incorporate multiple sensor data for improved water surface mapping.