Direction Errors Research Articles

Accounting for meteorological biases in simulated plumes using smarter metrics

Abstract. In the next few years, numerous satellites with high-resolution instruments dedicated to the imaging of atmospheric gaseous compounds will be launched, to finely monitor emissions of greenhouse gases and pollutants. Processing the resulting images of plumes from cities and industrial plants to infer the emissions of these sources can be challenging. In particular traditional atmospheric inversion techniques, relying on objective comparisons to simulations with atmospheric chemistry transport models, may poorly fit the observed plume due to modelling errors rather than due to uncertainties in the emissions. The present article discusses how these images can be adequately compared to simulated concentrations to limit the weight of modelling errors due to the meteorology used to analyse the images. For such comparisons, the usual pixel-wise ℒ2 norm may not be suitable, since it does not linearly penalise a displacement between two identical plumes. By definition, such a metric considers a displacement as an accumulation of significant local amplitude discrepancies. This is the so-called double penalty issue. To avoid this issue, we propose three solutions: (i) compensate for position error, due to a displacement, before the local comparison; (ii) use non-local metrics of density distribution comparison; and (iii) use a combination of the first two solutions. All the metrics are evaluated using first a catalogue of analytical plumes and then more realistic plumes simulated with a mesoscale Eulerian atmospheric transport model, with an emphasis on the sensitivity of the metrics to position error and the concentration values within the plumes. As expected, the metrics with the upstream correction are found to be less sensitive to position error in both analytical and realistic conditions. Furthermore, in realistic cases, we evaluate the weight of changes in the norm and the direction of the four-dimensional wind fields in our metric values. This comparison highlights the link between differences in the synoptic-scale winds direction and position error. Hence the contribution of the latter to our new metrics is reduced, thus limiting misinterpretation. Furthermore, the new metrics also avoid the double penalty issue.

State constrained control strategy for unmanned surface vehicle trajectory tracking based on improved barrier Lyapunov function

This paper addresses the state-constrained control of the symmetric underactuated unmanned surface vehicles (USVs) under unknown dynamics and time-varying interference based on improved Lyapunov function. Inspired by the prescribed performance control (PPC), the improved logarithmic barrier Lyapunov function (BLF) is proposed with a reasonably defined performance function in advance. The tracking errors of position and yaw direction are constrained within the set range. Meanwhile, the symmetric barrier Lyapunov function (SBLF) and dynamic surface control (DSC) are introduced to simplify the controller design and indirectly restrict the yaw velocity. On this basis, the finite-time disturbance observer (FDO) is proposed to estimate the unknown disturbance. The finite-time auxiliary dynamic system is introduced to deal with the input saturation. In addition, the neural network minimum learning parameter (MLP) can reduce the computational complexity while figuring out the unknown dynamics. Finally, numerical simulation verifies the effectiveness of the control system.

Multi-feature detection of in-field grain lodging for adaptive low-loss control of combine harvesters

The phenomenon of grain lodging significantly affects the low-loss harvesting performance of automatic drive harvesters, and it has become an objective trend to simultaneously detect multi-feature grain lodging information with machines in the field. In order to solve the problem of high harvest loss in grain lodging areas, we propose a new method for synchronous detection of grain lodging multi-feature information based on 3D point cloud data of a depth camera, in order to realize adaptive regulation of unmanned and low-loss harvesting. The multi-feature information of lodging grain is composed of lodging position, degree and direction, which can provide effective support information for the adaptive regulation of automatic driving harvesters. For the scene of grain harvesting operation with low contrast characteristics, we make full use of the environmental characteristics of the lodging areas that are located in the non-lodged area, and construct a synchronous airborne extraction strategy for grain lodging multi-feature information. The test results show that the maximum detection error of the lodging degree is less than 9.0 cm, and the minimum detection error is better than 1.0 cm; the maximum detection error of the lodging direction is not more than 9.0°, the minimum detection error is less than 1.0°, the maximum harvesting height error is less than 5.0 cm, and the minimum harvesting height error is less than 5.0 cm. Better than 2.0 cm. Our method provides an effective solution for synchronous airborne detection of multi-feature grain lodging information, which can significantly reduce harvest loss in grain lodging areas, and is expected to accelerate the development of truly unmanned harvesting operations.

Towards Digital Twin Implementation in Roll-To-Roll Gravure Printed Electronics: Overlay Printing Registration Error Prediction Based on Printing Process Parameters

Roll-to-roll gravure (R2Rg) has become highly affiliated with printed electronics in the past few years due to its high yield of printed thin-film transistor (TFT) in active matrix devices, and to its low cost. For printing TFTs with multilayer structures, achieving a high-precision in overlay printing registration accuracy (OPRA) is a key challenge to attain the high degree of TFT integration through R2Rg. To address this challenge efficiently, a digital twin paradigm was first introduced in the R2Rg system with an aim to optimize the OPRA by developing a predictive model based on typical input variables such as web tension, nip force, and printing speed in the R2Rg system. In our introductory-level digital twin, errors in the OPRA were collected with the variable parameters of web tensions, nip forces, and printing speeds from several R2Rg printing processes. Subsequently, statistical features were extracted from the input data followed by the training of a deep learning long-short term memory (LSTM) model for predicting machine directional error (MD) in the OPRA. As a result of training the LSTM model in our digital twin, its attained accuracy of prediction was 77%. Based on this result, we studied the relationship between the nip forces and printing speeds to predict the MD error in the OPRA. The results indicated a correlation between the MD error in the OPRA and the printing speed, as the MD error amplitude in the OPRA tended to decline at the higher printing speed.

Explicit Identification of Pointwise Terrain Gradients for Speed Compensation of Four Driving Tracks in Passively Articulated Tracked Mobile Robot

Tracked mobile robots can overcome the limitations of wheeled and legged robots in environments, such as construction and mining, but there are still significant challenges to be addressed in terms of trajectory tracking. This study proposes a kinematic strategy to improve the trajectory-tracking performance of a PASTRo (Passively Articulated Suspension based Track-typed mobile robot), which comprises four tracks, two rockers, a differential gear, and a main body. Due to the difficulties in explicitly identifying track-terrain contact angles, suspension kinematics is used to identify track-terrain contact angles (TTCA) in arbitrarily rough terrains. Thus, the TTCA-based driving velocity projection method is proposed in this study to improve the maneuverability of PASTRo in arbitrarily rough terrains. The RecurDyn-Simulink co-simulator is used to examine the improvement of PASTRo compared to a tracked mobile robot non-suspension version. The results indicate that PASTRo has a 33.3% lower RMS(Root Mean Square) distance error, 56.3% lower RMS directional error, and 43.2% lower RMS offset error than the four-track skid-steer mobile robot (SSMR), even with planar SSMR kinematics. To improve the maneuverability of PASTRo without any information on the rough terrain, the TTCA is calculated from the suspension kinematics, and the TTCA obtained is used for both TTCA-based driving velocity projection methods. The results show that PASTRo, with the TTCA-based driving velocity projection method, has a 39.2% lower RMS distance error, 57.9% lower RMS directional error, and 51.9% lower RMS offset error than the four-track SSMR.

Evaluation of Sea Surface Wind Products from Scatterometer Onboard the Chinese HY-2D Satellite

The Chinese new marine dynamic environment satellite HY-2D was launched on 19 May 2021, carrying a Ku-band scatterometer (named HSCAT-D). In this study, wind products observed by the HSCAT-D were validated by comparing with wind data from the U.S. National Data Buoy Center (NDBC) buoys and European Centre for Medium-Range Weather Forecasts (ECMWF) model. The statistical results show that the HSCAT-D winds have a good agreement with the buoys’ wind measurements: in comparison with buoy winds, the wind speed standard deviation (STD) and root-mean-squared errors (RMSE) of direction were 0.78 m/s and 14.10°, respectively. Other scatterometers’ wind data are also employed for comparisons, including the HY-2B scatterometer (HSCAT-B), HY-2C scatterometer (HSCAT-C), and MetOp-B scatterometer (ASCAT-B) winds. The statistical results indicate that errors for HSCAT-D winds are smaller than HSCAT-C but a little bit larger than HSCAT-B. The spectral analysis shows that the HSCAT-D wind products contain less small-scale information than ASCAT-B. Moreover, the Extended Triple Collocation (ETC) results show that the HSCAT-D wind product is of good quality and well-calibrated. We believe that the HSCAT-D wind products will be helpful for the scientific community, as shown by the encouraging validation results.

Evaluation of corrective effect of 6 degree of freedom couch on setup errors in intensity modulated radiotherapy for postoperative rectal cancer patients.

To explore the corrective effect of 6 degree of freedom couch on rotation errors in intensity modulated radiotherapy (IMRT) for postoperative rectal cancer patients, further to probe into the clinical application value of 6 degree of freedom couch in radiotherapy. From January 1, 2020 to December 1, 2020, 30 patients with rectal cancer receiving postoperative intensity modulated radiotherapy in The First Hospital of Hebei Medical University were included in this retrospective study. The setup error values in all direction of patients before and after 6 degree of freedom correction were collected during each radiotherapy session. In this study, a total of 382 data before and after the correction of 6 degree of freedom couch were collected. It was found that the setup errors in the Y direction gradually increased, was maximal in the third week, and then became smaller, and the setup errors in the other directions increased with the extension of radiotherapy time and reached the maximum at the 5th week. In the translation direction, the setup errors value in Z direction occurred more frequently than that in X and Y directions between the range of 0.21-0.80cm. In the rotation direction, the setup errors value in rotation X direction occurred more frequently than that in rotation Y and Z directions between the range of 0.21°-2.99°. In addition, after the correction of the 6 degree of freedom couch in real time, the setup errors in patients were significantly reduced in all directions (P < 0.05). In summary, it was recommended to clinically use 6 degree of freedom couch combined with IMRT for real-time correction of placement errors in patients with rectal cancer undergoing radiotherapy. At the same time, it was necessary to observe the tumor size and body weight changes of patients on the 5th week. If necessary, radiotherapy positioning and planning should be performed in time.

Towards cognitive navigation: A biologically inspired calibration mechanism for the head direction cell network

To derive meaningful navigation strategies, animals have to estimate their directional headings in the environment. Accordingly, this function is achieved by the head direction cells that were found in mammalian brains, whose neural activities encode one’s heading direction. It is believed that such head direction information is generated by integrating self-motion cues, which also introduces accumulative errors in the long term. To eliminate such errors, this paper presents an efficient calibration model that mimics the animals’ behavior by exploiting visual cues in a biologically plausible way, and then implements it in robotic navigation tasks. The proposed calibration model allows the agent to associate its head direction and the perceived egocentric direction of a visual cue with its position and orientation, and therefore to calibrate the head direction when the same cue is viewed again. We examine the proposed head direction calibration model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of quick association of information to proximal or distal cues as well as accuracy of calibrating the integration errors of the head direction. Videos can be viewed at https://videoviewsite.wixsite.com/hdc-calibration.

A Novel Multiresonant Chipless RFID Tag for Directional Strain Measurement on Metal Surface

In this article, a radio frequency identification (RFID) sensor tag for real-time health monitoring of the magnitude and direction of metal surface strain is presented. The chipless RFID sensor tag is composed of metal foil and F4B substrate, which is low-cost and works stably in harsh environments for a long time. Through highly sensitive strain monitoring, the risk can be predicted in the early stage of defect generation. The proposed tag includes a C-type resonator array, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> -type transmission line, and tag antennas. The C-type resonator has different sensitivities in the electrical length direction and width direction. Then, based on this characteristic, the resonator array creates a plurality of characteristic signatures containing strain information by optimizing the geometric parameters of the resonators. The strain information is transmitted to the tag antenna through the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> -type transmission line to complete the wireless communication between the tag and the reader. Finally, the performance of the strain monitoring system is verified by an experimental study. The experiment shows that the average sensitivity of the resonators is −4.94 and 1.14 kHz/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> in the electric length and width directions, respectively. When the strain is more than 150 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> , the relative error of magnitude is less than 12.7% and the absolute error of direction is less than 13.3°. Therefore, the proposed chipless RFID tag can monitor the amplitude and direction of strain with higher sensitivity and a simpler structure, for the key structures, such as the high-speed running gear.

Clinical Saccadometry: Establishing Evaluative Standards Using a Simplified Video Oculography Protocol in the Adult Population.

Saccadometry is an advanced ocular motor test battery that allows for the functional evaluation of the varied brain regions and circuits involved in the generation of fast, purposeful, and accurate saccadic eye movements. The test battery is composed of prosaccade (PS) and antisaccade (AS) tests that progressively increase cognitive demand. Existing saccadometry protocols qualitatively describe trends across the lifespan, but have not been widely adopted by clinicians. The aims of this study are to design an efficient and simplified clinical saccadometry protocol using video oculography (VOG) equipment and establish associated evaluative standards across the lifespan. Data were reported on 273 adults ages 18 to 69 years. Evaluative data on four measures: directional error rate (DE), latency (Lat), peak velocity (Vel), and accuracy (Acc) during PS and AS measurements were provided. Age-group differences were found in Lat (p < 0.01) and Vel (p = 0.04) during PS and age-group differences were found in DE (p = 0.04), Lat (p < 0.01) and Vel (p < 0.01) during AS. Gender differences were found in DE (p = 0.01) and Lat (p < 0.01) during AS. This study established a standardized and time-efficient protocol with evaluative standards for individuals ages 18 to 69 years old to enable the use of saccadometry as an objective measure in the clinic. Saccadometry allows clinicians to look beyond the traditional saccade test and evaluate complex oculomotor and cognitive functions that will better help clinicians differentiate between peripheral and central diagnoses.

Direction and distance information in memory for locations of objects relative to landmarks and boundaries.

An observer often remembers an object's location on the basis of its direction and distance from reference objects. Two kinds of reference object are of particular interest: landmarks and boundaries. We compared how well observers remembered the direction and distance of target objects from a landmark and a boundary. Patterns of variable error implied that the landmark was more effective than the boundary in supporting memory for target object direction. When the predictions of the landmark and the boundary were placed in conflict, patterns of constant error implied that the boundary was more effective than the landmark in supporting memory for target object distance. These results suggest affinities between direction information and landmarks and between distance information and boundaries. They raise the possibility that, rather than collapsing across direction and distance error, theoretical analyses should distinguish the two kinds of error in assessing the reliability of landmarks and boundaries.

Passive Joint Emitter Localization with Sensor Self-Calibration

This paper studies the problem surrounding distributed passive arrays (sensors) locating multiple emitters while performing self-calibration to correct possible errors in the assumed array directions. In our setting, only the angle-of-arrival (AoA) information is available for localization. However, such information may contain bias due to array directional errors. Hence, localization requires self-calibration. To achieve both, the key element behind our approach is that the received signals from the same emitter should be geometrically consistent if sensor arrays are successfully calibrated. This leads to our signal model, which is built on a mapping directly from emitter locations and array directional errors to received signals. Then we formulate an atomic norm minimization and use group sparsity to promote geometric consistency and align ‘ghost’ emitter locations from calibration errors. Simulations verify the effectiveness of the proposed scheme. We derive the Cramér Rao lower bound and numerically compare it to the simulations. Furthermore, we derive a necessary condition as a rule of thumb to decide the feasibility of joint localization and calibration.

The impact of traumatic brain injury on inhibitory control processes assessed using a delayed antisaccade task

It has been well established that traumatic brain injury (TBI) can affect cognitive function such as attention, working memory and executive functions. In the present study, we further investigated TBI-related changes in cognitive functions by investigating the ability to reorient visuospatial attention using a modified antisaccade task. Performing an antisaccade requires disengaging attention, inhibiting a reflexive saccade, and then engaging attention to execute a voluntary saccade in a direction opposite to a peripheral target. Particularly we quantified the time (latency), and accuracy (directional and disinhibition errors) of 26 TBI and 33 normal participants in making an antisaccade after a variable period of delay (0, 0.0625, 0.125, 0.250, 0.500 or 1.0 s). Changing the delay period allowed to systematically quantify the temporal and spatial characteristics of preparing and initiating an antisaccade and whether this process is affected by TBI. TBI participants took longer (approximately 33–66 ms for variable delays) to generate correct delayed antisaccades and showed increased directional errors (2–11 % for variable delays) and increased disinhibition prosaccade errors (2–6 % for variable delays) compared to controls. However, both groups made similar disinhibition antisaccade errors. These findings indicate that TBI participants required a longer time to process information, and a possible poorer response inhibition and poor spatial information processing due to head injury.

Photonics-assisted simultaneous detection of distances and directions for multi-targets based on polarization multiplexing and spectrum symmetry

A photonics-assisted simultaneous detection method of distances and directions for multiple targets is proposed based on polarization multiplexing and spectrum symmetry. A linear frequency modulation transmitting signal is generated by photonic frequency doubling. The echo signals are received by a three-antenna based linear array. The intermediate antenna supplies overlapped reference spectra by orthogonal modulation. According to specific spectrum symmetry, the de-chirped frequencies of echo signals from each target are clearly distinguished through polarization demultiplexing. Thus, distances and directions can be decoupled for multi-targets without direction ambiguity. Three-target proof-of-concept experiments have verified that the average measurement errors of distance and direction are 3.7 cm and 0.39°. The direction measurement range is up to 166.78°. A multi-target detection scheme with a large direction range is provided for the complex electromagnetic environment.

A Modeling Method for a 6-SPS Perpendicular Parallel Micro-Manipulation Robot Considering the Motion in Multiple Nonfunctional Directions and Nonlinear Hysteresis

Abstract Precision motion systems that call for an ultrahigh resolution are widely used in ultrahigh-precision engineering applications. In this article, a 6-SPS perpendicular compliant parallel micro-manipulation robot is presented. It is difficult to establish the mapping relationship between the applied voltage and end-effector pose due to the existence of compliant joints and piezoelectric actuators. A modeling method for a 6-SPS perpendicular compliant parallel micro-manipulation robot considering the motion in nonfunctional directions and hysteresis effect is proposed to reflect the characteristic from input voltage to output pose. The motion of the spherical compliant joint is regarded as a spatial six degrees-of-freedom mechanism. This method considers the motion errors in multiple nonfunctional directions of the compliant joints. The internal force and torque are also taken into account based on the spatial force and moment balance condition. The slow, fast dynamic modes, and hysteresis nonlinearity behavior are described using a series and parallel hybrid model structures. The kinematic model and compliance model without considering the motion in nonfunctional directions are conducted for comparison. Simulation results show that the presented modeling method has higher modeling accuracy. Finally, experiments on a 6DOF compliant parallel micro-manipulation robot reveal the fine modeling performance of the developed method for the precision motion systems in the presence of intrinsic hysteresis effect and motion error of compliant joints.

High-precision geomagnetic directional technology based on sensor error correction and adaptive hybrid filter

Low-cost magnetic and inertial sensors based on micro-electro-mechanical systems (MEMS) are extensively used for navigation systems. However, measurements of the magnetometer are very susceptible to different factors, resulting in low accuracy when used for attitude estimation. To solve these problems, a novel method is proposed for geomagnetic directional technology based on sensor error correction and adaptive hybrid filter. In the dynamic directional accuracy test with the turntable rotating speed of 40°/s, the maximum error and RMSE of the yaw angle is 1.00° and 0.63°, respectively. When magnetic interference exists, this algorithm dynamically adjusts the weighting of the magnetometer data by information entropy and RMSE. The experimental results show that the adaptive attitude updating algorithm can reduce the directional error by 90.61% in the environment of magnetic interference. It can meet the overall demand for high-precision attitude calculation of different carriers.

A Method for Studying Social Signal Learning of the Waggle Dance in Honey Bees.

Honey bees use a complex form of spatial referential communication. Their waggle dance communicates to nestmates the direction, distance, and quality of a resource by encoding celestial cues, retinal optic flow, and relative food value into motion and sound within the nest. This protocol was developed to investigate the potential for social learning of this waggle dance. Using this protocol, we showed that correct waggle dancing requires social learning. Bees (Apis mellifera) that did not follow any dances before they first danced produced significantly more disordered dances, with larger waggle angle divergence errors, and encoded distance incorrectly. The former deficits improved with experience, but distance encoding was set for life. The first dances of bees that could follow other dancers had none of these impairments. Social learning, therefore, shapes honey bee signaling, as it does communication in human infants, birds, and multiple other vertebrate species. However, much remains to be learned about insects' social learning, and this protocol will help to address knowledge gaps in the understanding of sophisticated social signal learning, particularly in understanding the molecular bases for such learning. Key features It was unclear if honey bees (Apis mellifera) could improve their waggle dance by following experienced dancers before they first waggle dance. Honey bees perform their first waggle dances with more errors if they cannot follow experienced waggle dancers first. Directional and disorder errors improved over time, but distance error was maintained. Bees in experimental colonies continued to communicate longer distances than control bees. Dancing correctly, with less directional error and disorder, requires social learning. Distance encoding in the honey bee dance is largely genetic but may also include a component of cultural transmission.

Assessing Potential Performance of GPS and Galileo in context of Broadcast Precise Orbits and Clock Corrections

The global navigation satellite system (GNSS) is becoming a vital positioning technology across various services. The ephemeris quality is one of the factors that directly impact the user's position accuracy. Some applications, such as investigations into Earth's crustal dynamics, need more precise ephemeris data than broadcast ephemeris. Several institutions, such as the international GNSS service (IGS), have developed precise orbital services to enable these applications. Unfortunately, data rates for such precise orbits are often confined to 15 minutes. In this paper, in order to generate precise ephemeris with the broadcast sampling period, the well-known Lagrange interpolation method is used. Furthermore, a comparative GPS and Galileo position analysis corresponding to the broadcast and precise ephemeris over a typical day in September 2021 is presented. To get insight into comparative positioning analysis over Hyderabad Station, the ENU (East-North-Up) directional errors, satellite visibility and horizontal accuracy parameters are considered. Based on the numerical analysis, standalone Galileo has similar capabilities to GPS, and it can be used in Multi-GNSS over India and its surrounding areas. This work may help in the development of single- or dual-frequency GNSS receivers for civilian navigation services.

Differences in China Greening Characteristics and its Contribution to Global Greening

With the rapid emergence of the global greening phenomenon under remote sensing monitoring, the prevailing trend of phenomenon analysis and traceability research is self-evident. However, identifying characteristics is basic research of the greening phenomenon, which sometimes subverts research results. The choice of method may directly affect the difference in the greening-browning range, which is easily overlooked. At the same time, influenced by the regional vegetation state’s basic value, the greening contribution’s spatialization still needs to be further verified. Based on the enhanced vegetation index results at the global kilometer-grid scale, this research chose to use the maximum value composite and the simple average method to explore the differences in China’s characteristic identification process initially. While paying attention to results and phenomena, scholars’ attention to basic research needs further improvement. The results show that the widely used two groups of basic methods have shown noticeable differences in greening and browning, and are affected by human activities, climate, geographical environment, etc. And this directional error and the phenomenon of hasty generalization are the most easily ignored in much basic research. The vegetation information considering the inherent stock and changing flux has quantified the greening contribution between regions. China, Brazil, and India dominate global greening, and Canada significantly contributes to browning. Some regions must promote the greening trend of changing flux while maintaining the inherent stock advantage.

Adaptation of QES-Fire, a dynamically coupled fast response wildfire model for heterogeneous environments

Background Modelling of fire front progression is challenging due to the large range of spatial and temporal scales involved in the interactions between the atmosphere and fire fronts. Further modelling complications arise when heterogeneous terrain and fuels are considered. Aims The aim of this study was to create a new parameterisation for wildfire-induced winds that accounts for the effects of heterogeneous terrain and fuels within the QES-Fire modelling framework – a fast-response wildfire model. Methods QES-Fire’s new turbulent plume merging model allows for distinct plumes to be merged together from fires burning in heterogeneous terrain with heterogeneous fuels. Additionally, fuel inputs from the LANDFIRE database developed for the Rothermel rate of spread (ROS) model, are translated to the Balbi ROS model. Key results The model was evaluated against the forested RxCADRE field experiment, with and without the effects of heterogeneity. Inclusion of heterogeneity reduced the relative error in burned area from 36 to 6%. Conclusions Small variations in terrain and fuel heterogeneity lead to large errors in rate and direction of fire front spread. Implications The modelled effects of terrain and fuel heterogeneity indicated the importance of capturing the complex coupled wildfire–atmospheric dynamics at the fire front.