Verification Points Research Articles

Prediction of potential cysteine synthase inhibitors of Leishmania braziliensis and Leishmania major parasites by computational screening

Leishmaniasis is a neglected tropical disease considered a public health problem that requires innovative strategies for its chemotherapeutic control. In the present investigation, a molecular docking approach was carried out using the protein cysteine synthase (CS) of Leishmania braziliensis (CSLb) and Leishmania major (CSLm) parasites to identify new compounds as potential candidates for the development of selective leishmaniasis therapy. CS protein sequence similarity, active site, structural modeling, molecular docking, and ADMET properties of compounds were analyzed using bioinformatics tools. Molecular docking analyses identified 1000 ligands with highly promising binding affinity scores for both CS proteins. A total of 182 compounds for CSLb and 173 for CSLm were selected for more detailed characterization based on the binding energy and frequency values and ADMET properties. Based on Principal Component Analysis (PCA) and K-means clusterization for both CS proteins, we classified compounds into 5 clusters for CSLb and 7 for CSLm, thus providing an excellent starting point for verification of enzyme inhibition in in vitro studies. We found the ZINC16524774 compound predicted to have a high affinity and stability for both CSLb and CSLm proteins, which was also evaluated through molecular dynamics simulations. Compounds within each of the five clusters also displayed pharmacological and structural properties that make them attractive drug candidates for the development of selective cutaneous leishmaniasis chemotherapy.

Accuracy Assessment of UAV-Photogrammetric-Derived Products Using PPK and GCPs in Challenging Terrains: In Search of Optimized Rockfall Mapping

Unmanned aerial photogrammetric surveys are increasingly being used for mapping and studying natural hazards, such as rockfalls. Surveys using unmanned aerial vehicles (UAVs) can be performed in remote, hardly accessible, and dangerous areas, while the photogrammetric-derived products, with high spatial and temporal accuracy, can provide us with detailed information about phenomena under consideration. However, as photogrammetry commonly uses indirect georeferencing through bundle block adjustment (BBA) with ground control points (GCPs), data acquisition in the field is not only time-consuming and labor-intensive, but also extremely dangerous. Therefore, the main goal of this study was to investigate how accurate photogrammetric products can be produced by using BBA without GCPs and auxiliary data, namely using the coordinates X0, Y0 and Z0 of the camera perspective centers computed with PPK (Post-Processing Kinematic). To this end, orthomosaics and digital surface models (DSMs) were produced for three rockfall sites by using images acquired with a DJI Phantom 4 RTK and the two different BBA methods mentioned above (hereafter referred to as BBA_traditional and BBA_PPK). The accuracy of the products, in terms of the Root Mean Square Error (RMSE), was computed by using verification points (VPs). The accuracy of both BBA methods was also assessed. To test the differences between the georeferencing methods, two statistical test were used, namely a paired Student’s t-test, and a non-parametric Wilcoxon signed-rank. The results show that the accuracy of the BBA_PPK is inferior to that of BBA_traditional, with the total RMSE values for the three sites being 0.056, 0.066, and 0.305 m, respectively, compared to 0.019, 0.036 and 0.014 m obtained with BBA_traditional. The accuracies of the BBA methods are reflected in the accuracy of the orthomosaics, whose values for the BBA_PPK are 0.039, 0.043 and 0.157 m, respectively, against 0.029, 0.036 and 0.020 m obtained with the BBA_traditional. Concerning the DSM, those produced with the BBA_PPK method present accuracy values of 0.065, 0.072 and 0.261 m, respectively, against 0.038, 0.060 and 0.030 m obtained with the BBA_traditional. Even though that there are statistically significant differences between the georeferencing methods, one can state that the BBA_PPK presents a viable solution to map dangerous and exposed areas, such as rockfall transit and deposit areas, especially for applications at a regional level.

Integrating Land-Cover Products Based on Ontologies and Local Accuracy

Freely available satellite imagery improves the research and production of land-cover products at the global scale or over large areas. The integration of land-cover products is a process of combining the advantages or characteristics of several products to generate new products and meet the demand for special needs. This study presents an ontology-based semantic mapping approach for integration land-cover products using hybrid ontology with EAGLE (EIONET Action Group on Land monitoring in Europe) matrix elements as the shared vocabulary, linking and comparing concepts from multiple local ontologies. Ontology mapping based on term, attribute and instance is combined to obtain the semantic similarity between heterogeneous land-cover products and realise the integration on a schema level. Moreover, through the collection and interpretation of ground verification points, the local accuracy of the source product is evaluated using the index Kriging method. Two integration models are developed that combine semantic similarity and local accuracy. Taking NLCD (National Land Cover Database) and FROM-GLC-Seg (Finer Resolution Observation and Monitoring-Global Land Cover-Segmentation) as source products and the second-level class refinement of GlobeLand30 land-cover product as an example, the forest class is subdivided into broad-leaf, coniferous and mixed forest. Results show that the highest accuracies of the second class are 82.6%, 72.0% and 60.0%, respectively, for broad-leaf, coniferous and mixed forest.

Vibration fatigue analysis of circumferentially notched specimens under coupled multiaxial random vibration environments

AbstractThe time domain critical plane‐based Carpinteri et al. criterion and the Theory of the Critical Distance are here combined together to propose a novel procedure for vibration fatigue analysis of circumferentially notched specimens subjected to coupled multiaxial random vibration environments. A novel metallic testing equipment is specially devised for notched specimens; meanwhile, a biaxial random vibration environment fatigue test is specially implemented on notched specimens in order to investigate how both coherence and phase shift between the auto‐spectral density functions in different directions influence the specimen fatigue life. The location of the verification point where to perform the fatigue damage estimation is determined by applying both the point method and the Carpinteri et al. criterion (for damage evaluation). The obtained results prove that the proposed procedure can provide satisfactory fatigue life estimations.

The Use of UAV Photogrammetric Technology in Order to Make the Cadastral Documentation of Detachment in Two Lots of a Property Located in Valea Ierii, Cluj County

The cadastre and the land book form a unitary and mandatory system that ensures technical, economic and legal records of all the properties on the territory of the country. This paper includes the presentation of the operations necessary to prepare the cadastral documentation for detachment in two lots, using UAV photogrammetric technology. The studied area is located in the suburbs of Valea Ierii locality, with an area of 212353 sqm. The main part of the project was based on the use of the UAV photogrammetric method to survey the area. At the same time, two GNSS receivers were used to complete the photogrammetric measurements. Control and verification points were premarked on the ground, the coordinates of which were determined by the real-time kinematic GNSS method. This operation was followed by performing the photogrammetric flight using an UAS platform. The flight lasted about 17 minutes, covered an area of 29 ha and 288 frames were captured. The front overlap between photos was set to 75% and the side overlap to 65%. New technologies for taking frames and processing them have been adopted, through methods that involve a low cost and a shorter time to perform specific operations.

Age and helium content of the open cluster NGC 6791 from multiple eclipsing binary members

Context. Models of stellar structure and evolution can be constrained using accurate measurements of the parameters of eclipsing binary members of open clusters. Multiple binary stars provide the means to tighten the constraints and, in turn, to improve the precision and accuracy of the age estimate of the host cluster. In the previous two papers of this series, we have demonstrated the use of measurements of multiple eclipsing binaries in the old open cluster NGC 6791 to set tighter constraints on the properties of stellar models than was previously possible, thereby improving both the accuracy and precision of the cluster age. Aims. We identify and measure the properties of a non-eclipsing cluster member, V56, in NGC 6791 and demonstrate how this provides additional model constraints that support and strengthen our previous findings. Methods. We analyse multi-epoch spectra of V56 from FLAMES in conjunction with the existing photometry and measurements of eclipsing binaries in NGC6971. Results. The parameters of the V56 components are found to be Mp = 1.103 ± 0.008 M⊙ and Ms = 0.974 ± 0.007 M⊙, Rp = 1.764 ± 0.099 R⊙ and Rs = 1.045 ± 0.057 R⊙, Teff,p = 5447 ± 125 K and Teff,s = 5552 ± 125 K, and surface [Fe/H] = +0.29 ± 0.06 assuming that they have the same abundance. Conclusions. The derived properties strengthen our previous best estimate of the cluster age of 8.3 ± 0.3 Gyr and the mass of stars on the lower red giant branch (RGB), which is MRGB = 1.15 ± 0.02 M⊙ for NGC 6791. These numbers therefore continue to serve as verification points for other methods of age and mass measures, such as asteroseismology.

Predicting article citations using data of 100 top-cited publications in the journal Medicine since 2011: A bibliometric analysis.

Publications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations. The citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients = 0.49, t = 5.62). The breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.

Remote estimation of total phosphorus concentration in the Taihu Lake using a semi-analytical model

ABSTRACT Eutrophication is a severe environmental problem in the most inland lakes. Taihu Lake, the third largest freshwater lake in China, is one of the most eutrophic lakes. Increased phosphorus concentration is thought to be the primary cause of water eutrophication. Proper total phosphorus (TP) monitoring is essential to effectively manage eutrophication in the Taihu Lake. In this study, 216 sample points with 172 modelling points and 44 verification points acquired from 5 field experiments in Taihu Lake, a semi-analytical model was established for estimating the TP concentration based on the absorption coefficient, with the mean absolute percentage error (MAPE) and root mean square error (RMSE) as 16.8% and 0.04 mg L−1, respectively. The application of the model on Sentinel-3 Ocean and Land Colour Instrument (OLCI) data proved the suitability of the model for satellite image with the MAPE and RMSE as 28.56% and 0.05 mg L−1. The OLCI derived TP concentration in the Taihu Lake shown the unique temporal and spatial distribution: TP concentration in Zhushan Bay, Meiliang Bay, Gonghu Bay, and the western coastal regions was significantly higher than the eastern, the southern, and the centre areas. The concentration of TP in Taihu Lake was the highest in summer and the lowest in winter. Furthermore, the versatility of this method was validated by applying in the Hongze Lake and Qiandao Lake, which is a water body dominated by inorganic suspended matter and a clean water body in China with the MAPE and RMSE as 24.10%, 19.35% and 0.004 mg L−1, 0.014 mg L−1. The results of this study could provide a reference for future remote sensing estimation of TP concentration and inland water eutrophication researches.

Generation of crustal movement correction parameter considering valid period and accuracy guarantee

In recent years, due to the development of precise point positioning (PPP), the inconsistency of map and satellite positioning results due to crustal deformation has come to the surface. In order to solve this problem, a parameter for correcting the crustal deformation is necessary, and if it is provided as a service, the validity period and the accuracy guarantee are also necessary. In this research, we considered the validity period of parameters and the estimation method of the coordinates used for calculating the amount of crustal deformation and actually constructed the crustal movement correction parameter generation system and accuracy evaluation system. The parameters generated by this method are called semi-dynamic reduction (SD/R) parameters. As a result of evaluating the accuracy of SD/R parameters, we achieved a target accuracy of 4 cm at 98.3% verification points in the horizontal direction. Therefore, the effectiveness of the proposed method was shown.

Rapid generation of global forest cover map using Landsat based on the forest ecological zones

The easy and ready access to Landsat datasets and the ever-lowering costs of computing make it feasible to monitor the Earth’s land cover at Landsat resolutions of 30 m. However, producing forest-cover products rapidly and on a large scale, such as intercontinental or global, is still a challenging task. By utilizing the huge catalog of satellite imagery as well as the high-performance computing capacity of Google Earth Engine, we proposed an automated pipeline for generating 30-m resolution global-scale forest map from time-series of Landsat images. We describe the methods to create products of forest cover at a global scale. First, we partitioned the landscapes into subregions of similar forest type and spatial continuity. Then, a multisource forest/nonforest sample set was established for machine algorithm learning training. Finally, a random forest classifier algorithm was used to obtain samples automatically, extract the characteristics of satellite images, and establish the forest/nonforest classifier models. Taking Landsat8 images in 2018 as a case, a novel 30-m resolution global forest cover (GFC30) map has been produced. The result shows that by the end of 2018, the total forest area in the world was 3.71 × 109 ha. The accuracy evaluation of GFC30 for 2018 was carried out using verification points via stratified random sampling of a MODIS land cover map (MCD12C1 product in 2012) and verified on high-resolution satellite imagery (e.g., Google Earth). According to the validation result, the overall accuracy of GFC30 for 2018 is 90.94%.

A novel procedure for damage evaluation of fillet-welded joints

In the present paper, a novel procedure for fatigue resistance assessment of fillet-welded joints under complex random loading is proposed. It consists of two consecutive steps: (1) computation of the stress tensor at the verification point; (2) evaluation of damage and, consequently, fatigue life. The procedure exploits the multiaxial critical plane-based criterion by Carpinteri et al. for random loading. A case study, represented by a mechanical component of an arm sprayer used in agriculture, is examined in order to assess such a procedure. A comparison between experimental and numerical results in terms of crack nucleation location is performed.

Acoustic Emission Source Localization with Generalized Regression Neural Network Based on Time Difference Mapping Method

Acoustic emission (AE) source localization is a powerful detection method. Time Difference Mapping (TDM) method is an effective method for detecting defects in complex structures. The core of this method is to search for a point with the minimum distance away from the verification point in the time difference database. In Traditional Time Difference Mapping (T-TDM) method and Improved Time Difference Mapping (I-TDM) method, the larger database and denser grids allow the higher localization accuracy. If the location points are not included in the database, the localization accuracy of the T-TDM and I-TDM methods will be greatly affected. To solve the above problems, a new AE source localization method, Generalized Regression Neural Network Based on Time Difference Mapping (GRNN-TDM), is proposed to improve the localization accuracy in the study. In the proposed method, the time difference data of the sensor path on all nodes in the time difference mapping are used as the training input data and the coordinates of grid nodes are used as the training output data. After continuous learning and training, the neural network model predicts its possible source location with the time difference data collected from the verification point. In this paper, the localization of AE sources with T-TDM, I-TDM and GRNN-TDM methods was studied in four composite plates with different fiber layers and an aluminum plate with holes. The localization results showed that the localization accuracy of the GRNN-TDM method was higher than that of T-TDM and I-TDM methods.

MAPPING URBAN AREAS USING DENSE TIME SERIES OF LANDSAT IMAGES AND GOOGLE EARTH ENGINE

Abstract. Urban information extraction from satellite based remote sensing data could provide the basic scientific decision-making data for the construction and management of future cities. In particular, long-term satellite based remote sensing such as Landsat observations provides a rich source of data for urban area mapping. Urban area mapping based on the single-temporal Landsat observations is vulnerable to data quality (such as cloud coverage and stripe), and it is difficult to extract urban areas accurately. The composite of dense time series Landsat observations can significantly reduce the effect of data quality on urban area mapping. Multidimensional array is currently effective theory for geographic big data analysis and management, providing a theoretical basis for the composite of dense time series Landsat observations. Google Earth Engine (GEE) not only provides rich satellite based remote sensing data for the composite of dense time series data, but also has powerful massive data analysis capabilities. In the study, we chose Random Forest (RF) algorithm for the urban area extraction owing to its stable performance, high classification accuracy and feature importance evaluation. In this work, the study area is located in the central part of the city of Beijing, China. Our main data source is all Landsat8 OLI images in Beijing (path/row: 123/32) in 2017.Based on the multidimensional array for geographic big data theory and the GEE cloud computing platform, four commonly used reducer methods are selected to composite the annual dense time series Landsat 8 OLI data. After collecting the training samples, RF algorithm was selected for supervised classification, feature importance evaluation and accuracy verification for urban area mapping. The results showed that 1), compared with the single temporal image of Landsat 8 OLI, the quality of annual composite image was improved obviously, especially for urban extraction in cloudy areas; 2) for the evaluation results of feature importance based on RF algorithm, Coastal, Blue, NIR, SWIR1 and SWIR2 bands were the more important characteristic bands, while the Green and Red bands were comparatively less important; 3) the annual composite images obtained by the ee.Reducer.min, ee.Reducer.max, ee.Reducer.mean and ee.Reducer.median methods were classified and accuracy verification was carried out using the verification points. The overall accuracy of the urban area mapping reached 0.805, 0.820, 0.868 and 0.929, respectively. In summary, the ee.Reducer.median method is a suitable method for annual dense time series Landsat image composite, which could improve the data quality, and ensure the difference of features and the higher accuracy of urban area mapping.

Regulatory Study on Air Purification System of Medical Device Manufacturers

Objective Through regulatory study on the common defects of air purification system, this paper provides valuable reference for practitioners in medical device industry. Methods More than 100 verification results of different companies had been collected during 2015 to 2018, followed by systematically analysis of the defects related to air purification system. Result 70 types of common defects in 13 areas had been summarized, and 20 key points in verification had been briefly concluded. Conclusion Recognizing and understanding these summarized defects and key points will not only promote the unification of criterion scale, but also benefit enterprises for themselves, inspection, quality management improvement, and the plant transformation as well.

Comparative Study on Executing Topographic Plans Using UAVs

The present paper aims to carry out a comparative study on how the digital model can be obtained using the images taken with a camera mounted on a UAV, in two cases: The case where there are control points determined on the ground. The case where there are no control points determined on the ground. To verify the consistency of the digital model, field verification points were determined using GNSS receivers. Basically, on the same area of interest were carried out GNSS RTK measurements and two flights with two different types of UAVs: SenseFlyeBee X and DroneZone XF8-CT. The flight was carried out at the same height and with medium resolution cameras (Sony A7R 35 mm 36 Mpix and SenseFlyAeria X 24 MPix).The GNSS receivers were different. Thus, for the DroneZone XF8CT a GNSS receiver of the u-Blox NEO8M type was used and for SenseFlyeBee X a GNSS RTK receiver of the TRIMBLE BD 93 type and a SenseFly GeoBase base. To establish the consistency of the data, 28 verification points were measured on the ground with GNSS technology. The measurements for determining the position of the control points were performed on different days, using a Leica GS08 Plus GNSS system, connected to the National Network of Permanent GNSS Stations (RN-SGP) through the ROMPOS system. The flight made with DroneZone XF8-CT, 6 control points were determined. The flight made with SenseFlyeBee X, only the data taken by the RTK system from the SenseFlyeBee X UAV were used. The data were processed and a Digital Terrain Model was created for each flight. Finally, a comparison was made between the two Digital Terrain Models, in order to determine the differences between them, but also the differences as against the RTK verification measurements made with the Leica GS08 Plus GNSS system.

Point of Care Blood Gas Analyser Verification at the Largest Academic Hospital in Southern Hemisphere Revived by Coronavirus Calls for Tests to Be Verified

Introduction: At no point in the history of medicine has the importance of point-of-care testing (POCT) devices, tests and methods verification and utilisation been recognised and accepted than during the coronavirus pandemic. Blood gas analysers offer the best form of POCT and this has been demonstrated in the management of coronavirus patients admitted to hospital intensive care units with respiratory challenges. The new analysers were evaluated in compliance with the Clinical Laboratory Improvement Amendments (CLIA) regulation. The new method must be evaluated by comparison to the central laboratory or the outgoing analyser. The study was undertaken to verify if the new instrument, OMNI S b221 matches the well-established analysers currently in use at the hospital. Objectives: To evaluate method performance of pH, the partial pressure of carbon dioxide (pCO₂), the partial pressure of oxygen (pO₂), glucose, lactate, and electrolytes on OMNI S b221 blood gas analyser. Materials and Methods: To analyse the method performance of the pH, pO₂, pCO₂, glucose, lactate and electrolytes (Na⁺, K⁺ Ca⁺⁺) on OMNI S b221 blood gas analyser 40 samples run on OMNI S b221 blood gas analyser were compared with the results obtained from ABL700, GEM PREMIER for all the parameters and the Roche Hitachi 917 analyser to compare two electrolytes (Na⁺ and K⁺). The correlation coefficient was calculated for the results obtained from each paired set of instruments (ABL 700 vs GEM PREMIER and ABL 700 vs OMNI S b221). Comparability between analyser methods performance was determined using linear regression analysis. Results: The correlation coefficient between the paired analytical platforms were all between 0.81 and 0.99, demonstrating a strong linear relationship. The coefficient of variation for all the parameters were less than 2 also demonstrating good precision. Conclusion: OMNI S b221 blood gas analyser correlated well with the outgoing ABL 700, GEM PREMIER blood gas analyser and the central laboratory analyser, Roche Hitachi 917 and therefore, verified as a good platform to run arterial blood gas samples.

A Novel Mobile Wallet Model for Elderly Using Fingerprint as Authentication Factor

Due to the availability of fingerprint verification technology on mobile devices, fingerprint based human identification has become the most widely used biometric technology in everyday life. The elderly find digital payment applications difficult to operate and unsecure. This work has exploited fingerprint verification availability on mobile devices to provide a user friendly and secure digital wallet payment facility to elderlies who are unable to avail this facility due to the complex infrastructure of traditional authentication mechanisms. A novel digital payment mechanism is presented which uses Bluetooth technology of mobile devices for billing at the point of sale and fingerprint verification for user authentication. A proof of the concept study is presented to validate the proposed model using state of the art usability questionnaires and attributes with the target group. The result indicates that the proposed methodology provides satisfaction and ease of use to the user.

Study of Donghu Lake Water Eutrophication Simulation Based on Mike21

In this paper, a water environment numerical model of donghu lake is constructed based on MIKE21. Firstly, the hydrodynamic numerical model of donghu lake is established by FM module. A nonlinear triangular grid computing domain was created in the research area, initial boundary conditions and wind-driven data were set and other hydrodynamic parameters were input. The actual water level and velocity data in the part of research periods in December 2017 were used for model calibration and verification. Calibration results: vortex viscosity coefficient is 0.29 and manning constant is 0.42m1/3/s. The result of hydrodynamic simulation is in line with the actual situation. On this basis, the water quality module WQ was coupled to simulate the water quality of donghu lake. The simulation period is from November 15 to December 17, 2017.The measured water quality data on December 17 were selected for model calibration and verification, and the errors of each verification point were counted. The calculated results show that the simulated MSE of chlorophyll a concentration is 19.60%, and the simulated MSE of orthophosphate phosphorus is 25.36%. The overall simulation accuracy is well, which can reasonably show the changes of main water quality indexes in donghu lake.

Digital psychosocial assessment: An efficient and effective screening tool.

A large proportion of young people with chronic health conditions are surviving into adulthood. They face the same challenges as their healthy peers and are at increased risk of mental health problems. Psychosocial assessment is a crucial aspect of clinical care. Interviews using the internationally used and accepted HEEADSSS (home environment, education/employment, eating, peer-related activities, drugs, sexuality, suicide/depression, and safety) framework require trained clinicians, rapid interpersonal engagement, time and manual documentation. HEEADSSS-derived digital self-report surveys can be initiated by non-trained staff. This study compares the utility and information recorded using both methods. A retrospective analysis comparing documentation from HEEADSSS guided face-to-face interview and a digital survey tool was conducted using 146 records collected by the Trapeze transition service across the two locations of the Sydney Children's Hospital Network (NSW, Australia) between 2013 and 2016. A panel of four experts used an iterative process to identify 29 data verification points, falling into seven categories. Wilcoxon signed-rank tests were used to compare category scores. The digital survey took an average of 15 min and showed a significantly higher rate of disclosure across all psychosocial categories, particularly in the sensitive areas of emotions, drug use, sex and safety, compared to electronic medical record documentation of interview. Digital survey provided a time-efficient psychosocial screening tool that was self-administered, able to be introduced by non-trained staff, had a consistent record of responses, and elicited a substantially higher disclosure rate for important areas of strength and risk that may otherwise be avoided or not recorded.

Reconstructing One Kilometre Resolution Daily Clear-Sky LST for China’s Landmass Using the BME Method

The land surface temperature (LST) is a key parameter used to characterize the interaction between land and the atmosphere. Therefore, obtaining highly accurate, spatially consistent and temporally continuous LSTs in large areas is the basis of many studies. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST product is commonly used to achieve this. However, it has many missing values caused by clouds and other factors. The current gap-filling methods need to be improved when applied to large areas. In this study, we used the Bayesian maximum entropy (BME) method, which considers spatial and temporal correlation, and takes multiple regression results of the Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), longitude and latitude as soft data to reconstruct space-complete daily clear-sky LSTs with a 1 km resolution for China’s landmass in 2015. The average Root Mean Square Error (RMSE) of this method was 1.6 K for the daytime and 1.2 K for the nighttime when we simultaneously covered more than 10,000 verification points, including blocks that were continuous in space, and the average RMSE of a single discrete verification point for 365 days was 0.4 K for the daytime and 0.3 K for the nighttime when we covered four discrete points. Urban and snow land cover types have a higher accuracy than forests and grasslands, and the accuracy is higher in winter than in summer. The high accuracy and great ability of this method to capture extreme values in urban areas can help improve urban heat island research. This method can also be extended to other study areas, other time periods, and the estimation of other geographical attribute values. How to effectively convert clear-sky LST into real LST requires further research.