Various Sources Of Error Research Articles

Model assessment in scientific computing

PurposeThis paper aims to focus on the assessment of the ability of computer models with imperfect functional forms and uncertain input parameters to represent reality.Design/methodology/approachIn this assessment, both the agreement between a model’s predictions and available experiments and the robustness of this agreement to uncertainty have been evaluated. The concept of satisfying boundaries to represent input parameter sets that yield model predictions with acceptable fidelity to observed experiments has been introduced.FindingsSatisfying boundaries provide several useful indicators for model assessment, and when calculated for varying fidelity thresholds and input parameter uncertainties, reveal the trade-off between the robustness to uncertainty in model parameters, the threshold for satisfactory fidelity and the probability of satisfying the given fidelity threshold. Using a controlled case-study example, important modeling decisions such as acceptable level of uncertainty, fidelity requirements and resource allocation for additional experiments are shown.Originality/valueTraditional methods of model assessment are solely based on fidelity to experiments, leading to a single parameter set that is considered fidelity-optimal, which essentially represents the values which yield the optimal compensation between various sources of errors and uncertainties. Rather than maximizing fidelity, this study advocates for basing model assessment on the model’s ability to satisfy a required fidelity (or error tolerance). Evaluating the trade-off between error tolerance, parameter uncertainty and probability of satisfying this predefined error threshold provides us with a powerful tool for model assessment and resource allocation.

Measurements of the thermal conductivity of propane at the approach of the coexistence line

We report the first measurements of the thermal conductivity of propane which show a steep increase of the thermal conductivity when approaching the coexistence line, in vapor and liquid phases. Measurements of the thermal conductivity of propane were performed in a coaxial cylinder cell operating in steady state conditions. The measurements of the thermal conductivity of propane were carried out along six isotherms below the critical temperature of propane (369.825 K). The present data cover the temperature range from 364.65 K to 369.12 K, and the pressure range 0.1–15 MPa. The analysis of the various sources of error leads to an estimated uncertainty of approximately ±3%, near the saturation curve. In order to analyze the subcritical enhancement of the thermal conductivity as a function of temperature and density at the approach of the saturation curve, background equations were used.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

Abstract. Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data–space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

A Linearizing Digitizer for Wheatstone Bridge Based Signal Conditioning of Resistive Sensors

Output of a typical Wheatstone bridge, when it is connected to measure from a single or a dual resistive element, possesses non-linear characteristic. This paper presents a novel signal conditioning scheme, which provides a linear-digital output directly from the resistive sensor(s) that are connected in such bridge configurations. In the present scheme, the input stage of a dual-slope analog-to-digital converter (DSADC) is suitably augmented to incorporate the quarter-bridge and (or) half-bridge containing the resistive sensor as an integral part of the DSADC. A combination of the current mode excitation and wisely selected integration and de-integration operations of the DSADC enable to achieve linearization in the digitization process itself, leading to an overall reduction in the complexity level and number of blocks used keeping the high accuracy unaltered. A detailed analysis has been conducted to quantify the effect of various sources of errors in the output of the DSADC. The details are presented in the paper. The proposed method not only provides a linear digital output but also drastically reduces the effect on the output due to the lead wires that connect the Wheatstone bridge and the DSADC. Thus, the proposed scheme is well suited for the situations where the sensor(s) is (are) remotely located at a distance. Simulation studies as well as results from a prototype developed and tested establish the practicality of the proposed scheme. The inherent non-linearity of the Wheatstone bridge is reduced by nearly two orders of magnitude.

DNS and approximate deconvolution as a tool to analyse one-dimensional filtered flame sub-grid scale modelling

A procedure using approximate deconvolution and explicit filtering is discussed to evaluate topology-based sub-grid scale (SGS) combustion models. A direct numerical simulation (DNS) database is first filtered, then a deconvolution operator constructed from the topology-based SGS model is applied, to compare the approximate three-dimensional fields against the exact ones. The DNS is obtained from an already well-resolved large eddy simulation (LES) of a bunsen flame, by refining the mesh up to full resolution of the reaction zones and the turbulent flow scales. The SGS model evaluation via approximate deconvolution is applied to a flamelet-like closure based on the tabulation of filtered one-dimensional flames. The various sources of errors are analysed in a statistical manner in terms of flame topology. Aside from the a priori analysis, results from LES are also reported with the one-dimensional flame deconvolution and compared against those resulting from an approximate three-dimensional deconvolution, confirming the need for accounting for the full 3D flame dynamics in SGS modelling. All the study is performed with tabulated detailed chemistry.

Full and effective participation of indigenous peoples in forest monitoring for reducing emissions from deforestation and forest degradation (REDD+): trial in Panama's Darién

AbstractA primary technical requirement of the climate change mitigation mechanism, reducing emissions from deforestation and forest degradation (REDD+), is to calculate emissions factors, that is, the amount of CO2 emissions or removals per hectare from land use and land‐use change. Emissions factors are calculated from baseline estimates of the aboveground biomass (AGB) stored in different vegetation types. Ground‐based methods for estimating AGB, such as forest inventories, despite being relatively accurate and necessary for calibrating remotely sensed data such as satellite or airborne Light Detection and Ranging, tend to be expensive and time‐consuming. Thus, calls have been made to improve the cost‐efficiency of these methods within the context of REDD+. Also as part of REDD+, there have been calls for the legitimate inclusion of indigenous peoples and rural communities in various aspects of the mechanism. To address both of these issues, we devised a participatory, rapid, forest inventorying method and tested it across the heterogeneous forest landscape of Darién, Panama. This effort took place within a project that was administratively and logistically managed entirely by an indigenous organization working in collaboration with indigenous authorities in Darién, with funding from the World Bank. A group of 24 indigenous technicians were trained on forest inventorying methods. They established and measured thirty 1‐ha plots under our direct supervision. We tested for various sources of error in tree diameter and height measurements. We also tested the scalability of our tree‐level biomass estimates to the plot level by comparing our results with simulations conducted on the Barro Colorado Island 50‐ha permanent plot data. Results indicate that our rapid, participatory, forest inventorying method effectively captures plot‐level AGB, while guaranteeing the full and effective participation of indigenous peoples. The benefits of our method in terms of cost‐efficiency and access to remote forest areas are discussed, as well as those accrued by indigenous peoples.

Kalibrisanje konstitutivnih modela korišćenjem instrumentalnog utiskivanja i stohastičke inverzne analize

Indentation test is used with growing popularity for the characterization of various materials on different scales. Developed methods are combining the test with computer simulation and inverse analyses to assess material parameters entering into constitutive models. The outputs of such procedures are expressed as evaluation of sought parameters in deterministic sense, while for engineering practice it is desirable to assess also the uncertainty which affects the final estimates resulting from various sources of errors within the identification procedure. In this paper an experimental-numerical method is presented centered on inverse analysis build upon data collected from the indentation test in the form of force-penetration relationship (so-called 'indentation curve'). Recursive simulations are made computationally economical by an 'a priori' model reduction procedure. Resulting inverse problem is solved in a stochastic context using Monte Carlo simulations and non-sequential Extended Kalman filter. Obtained results are presented comparatively as for accuracy and computational efficiency.

A method to reconstruct and apply 3D primary fluence for treatment delivery verification.

MotivationIn this study, a method is reported to perform IMRT and VMAT treatment delivery verification using 3D volumetric primary beam fluences reconstructed directly from planned beam parameters and treatment delivery records. The goals of this paper are to demonstrate that 1) 3D beam fluences can be reconstructed efficiently, 2) quality assurance (QA) based on the reconstructed 3D fluences is capable of detecting additional treatment delivery errors, particularly for VMAT plans, beyond those identifiable by other existing treatment delivery verification methods, and 3) QA results based on 3D fluence calculation (3DFC) are correlated with QA results based on physical phantom measurements and radiation dose recalculations.MethodsUsing beam parameters extracted from DICOM plan files and treatment delivery log files, 3D volumetric primary fluences are reconstructed by forward‐projecting the beam apertures, defined by the MLC leaf positions and modulated by beam MU values, at all gantry angles using first‐order ray tracing. Treatment delivery verifications are performed by comparing 3D fluences reconstructed using beam parameters in delivery log files against those reconstructed from treatment plans. Passing rates are then determined using both voxel intensity differences and a 3D gamma analysis. QA sensitivity to various sources of errors is defined as the observed differences in passing rates. Correlations between passing rates obtained from QA derived from both 3D fluence calculations and physical measurements are investigated prospectively using 20 clinical treatment plans with artificially introduced machine delivery errors.ResultsStudies with artificially introduced errors show that common treatment delivery problems including gantry angle errors, MU errors, jaw position errors, collimator rotation errors, and MLC leaf position errors were detectable at less than normal machine tolerances. The reported 3DFC QA method has greater sensitivity than measurement‐based QA methods. Statistical analysis‐based Spearman's correlations shows that the 3DFC QA passing rates are significantly correlated with passing rates of physical phantom measurement‐based QA methods.ConclusionAmong measurement‐less treatment delivery verification methods, the reported 3DFC method is less demanding than those based on full dose re‐calculations, and more comprehensive than those that solely checks beam parameters in treatment log files. With QA passing rates correlating to measurement‐based passing rates, the 3DFC QA results could be useful for complementing the physical phantom measurements, or verifying treatment deliveries when physical measurements are not available. For the past 4+ years, the reported method has been implemented at authors’ institution 1) as a complementary metric to physical phantom measurements for pretreatment, patient‐specific QA of IMRT and VMAT plans, and 2) as an important part of the log file‐based automated verification of daily patient treatment deliveries. It has been demonstrated to be useful in catching both treatment plan data transfer errors and treatment delivery problems.

T1-refBlochi: high resolution 3D post-contrast T1 myocardial mapping based on a single 3D late gadolinium enhancement volume, Bloch equations, and a reference T1

BackgroundHigh resolution 3D T1 mapping is important for assessment of diffuse myocardial fibrosis in left atrium or other thin-walled structures. In this work, we investigated a fast single-TI 3D high resolution T1 mapping method that directly transforms a 3D late gadolinium enhancement (LGE) volume to a 3D T1 map.MethodsThe proposed method, T1-refBlochi, is based on Bloch equation modeling of the LGE signal, a single-point calibration, and assumptions that proton density and T2* are relatively uniform in the heart. Several sources of error of this method were analyzed mathematically and with simulations. Imaging was performed in phantoms, eight swine and five patients, comparing T1-refBlochi to a standard spin-echo T1 mapping, 3D multi-TI T1 mapping, and 2D ShMOLLI, respectively.ResultsThe method has a good accuracy and adequate precision, even considering various sources of error. In phantoms, over a range of protocols, heart-rates and T1 s, the bias ±1SD was -3 ms ± 9 ms. The porcine studies showed excellent agreement between T1-refBlochi and the multi-TI method (bias ±1SD = −6 ± 22 ms). The proton density and T2* weightings yielded ratios for scar/blood of 0.94 ± 0.01 and for myocardium/blood of 1.03 ± 0.02 in the eight swine, confirming that sufficient uniformity of proton density and T2* weightings exists among heterogeneous tissues of the heart. In the patients, the mean T1 bias ±1SD in myocardium and blood between T1-refBlochi and ShMOLLI was -9 ms ± 21 ms.ConclusionT1-refBlochi provides a fast single-TI high resolution 3D T1 map of the heart with good accuracy and adequate precision.

A kinetic model for the transport of electrons in a graphene layer

In this article, we propose a new numerical scheme for the computation of the transport of electrons in a graphene device. The underlying quantum model for graphene is a massless Dirac equation, whose eigenvalues display a conical singularity responsible for non-adiabatic transitions between the two modes. We first derive a kinetic model which takes the form of two Boltzmann equations coupled by a collision operator modeling the non-adiabatic transitions. This collision term includes a Landau–Zener transfer term and a jump operator whose presence is essential in order to ensure a good energy conservation during the transitions. We propose an algorithmic realization of the semi-group solving the kinetic model, by a particle method. We give analytic justification of the model and propose a series of numerical experiments studying the influences of the various sources of errors between the quantum and the kinetic models.

Quality assurance in quantitative MRI

There is a continuously evolving paradigm shift in MRI, that of quantitative MRI (qMRI). Therefore, a gradual transition exists from a simplified, phenomenological and descriptive procedure to a quantitative measurement used for early diagnosis, disease evaluation and monitoring, as well as for therapeutic guidance. There is a plethora of parameters that can be used as quantitative markers in MRI, ranging from relaxation times to indices related to complex mechanisms such as diffusion and perfusion. The advent of qMRI has introduced new concepts in clinical MRI practice such as sensitivity, accuracy and specificity. The measurement precision and accuracy can be determined through a carefully designed program of quality control employing both phantoms and healthy volunteers. The need for high specificity lies in choosing the optimal parameter to be measured and monitored. The main requirement for increasing the measurement’s sensitivity and accuracy and for achieving high sensitivity is to fully understand the underlying q-MRI mechanism. With regard to the various sources of error and inaccuracy involved, q-MRI can be divided into two sub-processes: data collection and data analysis. A quality assurance program has to address issues related to both sub-processes. The second one refers to post-processing and, thus, it is a repeatable process which can adopt suitable measures for mitigating pertinent inaccuracies. The former refers to scanning. Spatial distortions and signal inaccuracies stem from many factors related to the measurement conditions. It is essential, therefore, to characterize, reduce and correct these distortions and inaccuracies, so as not to adversely affect quantitative results.

Initial-data contribution to the error budget of gravitational waves from neutron-star binaries

As numerical calculations of inspiralling neutron-star binaries reach values of accuracy that are comparable with those of binary black holes, a fine budgeting of the various sources of error becomes increasingly important. Among such sources, the initial data is normally not accounted for, the rationale being that the error on the initial spacelike hypersurface is always far smaller than the one gained during the evolution. We here consider critically this assumption and perform a comparative analysis of the gravitational waveforms relative to essentially the same physical binary configuration when computed with two different initial-data codes, and then evolved with the same evolution code. More specifically, we consider the evolution of irrotational neutron-star binaries computed either with the pseudo-spectral code \lorene{}, or with the newly developed finite-difference code \cocal{}; both sets of initial data are subsequently evolved with the high-order evolution code \whiskythc{}. In this way we find that despite the initial data shows global (local) differences that are $\lesssim 0.02\%\ (1\%)$, the gravitational-wave phase at the merger time differs by $\sim 0.5$ radians after $\sim 3$ orbits, a surprisingly large value. Our results highlight the highly nonlinear impact that errors in the initial data can have on the subsequent evolution and the importance of using exactly the same initial data when comparative studies are done.

Tracking city CO<sub>2</sub> emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany

Abstract. Currently, 52 % of the world's population resides in urban areas and as a consequence, approximately 70 % of fossil fuel emissions of CO2 arise from cities. This fact, in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements, makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here, we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat) which was proposed to the European Space Agency (ESA) to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport. To achieve this, we use (i) a high-resolution modelling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG), which is used to simulate the atmospheric observations of column-averaged CO2 dry air mole fractions (XCO2), and (ii) a Bayesian inversion method to derive anthropogenic CO2 emissions and their errors from the CarbonSat XCO2 observations. We focus our analysis on Berlin, Germany using CarbonSat's cloud-free overpasses for 1 reference year. The dense (wide swath) CarbonSat simulated observations with high spatial resolution (approximately 2 km × 2 km) permits one to map the city CO2 emission plume with a peak enhancement of typically 0.8–1.35 ppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE) of the retrieved Berlin CO2 emission for a single overpass is typically less than 8–10 Mt CO2 yr−1 (about 15–20 % of the total city emission). The range of systematic errors (SEs) of the retrieved fluxes due to various sources of error (measurement, modelling, and inventories) is also quantified. Depending on the assumptions made, the SE is less than about 6–10 Mt CO2 yr−1 for most cases. We find that in particular systematic modelling-related errors can be quite high during the summer months due to substantial XCO2 variations caused by biogenic CO2 fluxes at and around the target region. When making the extreme worst-case assumption that biospheric XCO2 variations cannot be modelled at all (which is overly pessimistic), the SE of the retrieved emission is found to be larger than 10 Mt CO2 yr−1 for about half of the sufficiently cloud-free overpasses, and for some of the overpasses we found that SE may even be on the order of magnitude of the anthropogenic emission. This indicates that biogenic XCO2 variations cannot be neglected but must be considered during forward and/or inverse modelling. Overall, we conclude that a satellite mission such as CarbonSat has high potential to obtain city-scale CO2 emissions as needed to enhance our current understanding of anthropogenic carbon fluxes, and that CarbonSat-like satellites should be an important component of a future global carbon emission monitoring system.

ERROR INTRAOBSERVADOR EN EL ANÁLISIS PALEOHISTOLÓGICO DE SUPERFICIES CRANEOFACIALES

Fil: Brachetta Aporta, Natalia. Universidad Nacional de La Plata. Facultad de Cienicas Naturales y Museo. Division Antropologia; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas; Argentina

A Real-Time Automated Quality Control of Hourly Rain Gauge Data Based on Multiple Sensors in MRMS System

Abstract Automated rain gauge networks provide direct measurements of precipitation and have been used for numerous applications, such as generating regional and national precipitation maps, calibrating remote sensing quantitative precipitation estimation (QPE), and validating hydrological and meteorological model predictions. However, automated gauge observations are prone to be affected by a variety of error sources and require a careful quality-control (QC) procedure. Many previous gauge QC techniques were based on spatiotemporal checks within the gauge network itself, and their effectiveness can be dependent on gauge densities and precipitation regimes. The current study takes advantage of the multisensor data sources in the Multi-Radar Multi-Sensor (MRMS) system and develops an automated and computationally efficient gauge QC scheme based on the consistency of hourly gauge and radar QPE observations. Radar and gauge error characteristics related to radar sampling geometry, precipitation regimes, and freezing-level height is utilized within this scheme. This QC scheme is evaluated by testing its capability to identify suspect gauges and comparing the ability to quality-controlled gauges through statistical and spatial comparisons of gauge-influenced gridded QPE products. Spatial analysis of the gridded QPE products in MRMS resulted in a more physical spatial QPE distribution using quality-controlled gauges versus the same product created with non-quality-controlled gauge data.

An Easy-to-Interface CDC With an Efficient Automatic Calibration

A new capacitance-to-digital converter (CDC) that gives a digital output proportional to the measurand $kx$ , independent of its nominal capacitance, is reported in this paper. Various CDCs are available in the market, but their output is a function of the nominal value $C_{0}$ of the sensor. Thus, a manual correction is required in the output, whenever a new capacitive sensor is interfaced to such CDCs. Moreover, the $C_{0}$ of the sensors is usually a large value compared with the change in capacitance due to $kx$ . Thus, in a typical CDC, a large percentage of the output counts/bits is used to measure and represent the $C_{0}$ leading to an underutilization of the hardware as far as the measurement of $kx$ is concerned. The proposed CDC uses a new automatic calibration (AC), employing a switched-capacitor (SC) circuit-based voltage source in a feedback topology, and provides an output independent of the $C_{0}$ of the sensor employed. The proposed CDC is based on an SC dual-slope technique and possesses the advantages of the dual-slope conversion method. The CDC circuit is designed such that the entire full scale can be used for representing the change in the $kx$ . In addition to this advantage, the AC helps to remove the dependence on the accuracy of the reference capacitor employed in the CDC. A detailed analysis of the effect of various sources of errors in the CDC has been conducted and presented in this paper. A prototype of the proposed CDC has been developed and tested. The results obtained show that the output of the CDC is not a function of the $C_{0}~(C_{0}$ varied from 60 pF to 1.46 nF) of the sensors interfaced.

Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value

We propose a new class of computationally fast algorithms to find close to optimal policy for Markov Decision Processes (MDP) with large finite horizon T.The main idea is that instead of planning until the time horizon T, we plan only up to a truncated horizon H << T and use an estimate of the true optimal value function as the terminal value. Our approach of finding the terminal value function is to learn a mapping from an MDP to its value function by solving many similar MDPs during a training phase and fit a regression estimator. We analyze the method by providing an error propagation theorem that shows the effect of various sources of errors to the quality of the solution. We also empirically validate this approach in a real-world application of designing an energy management system for Hybrid Electric Vehicles with promising results.

Assessment of Numerical and Experimental Errors in Hybrid Simulation of Framed Structural Systems through Collapse

Hybrid simulation can provide significant advantages for large-scale experimental investigations of the seismic response of structures through collapse, particularly when considering cost and safety of conventional shake table tests. Hybrid simulation, however, has its own challenges and special attention must be paid to mitigate potential numerical and experimental errors that can propagate throughout the simulation. Several case studies are presented here to gain insight into the factors influencing the accuracy and stability of hybrid simulation from the linear-elastic response range through collapse. The hybrid simulations were conducted on a four-story two-bay moment frame with various substructuring configurations. Importantly, the structural system examined here was previously tested on a shake table with the same loading sequence, allowing for direct evaluation of the hybrid simulation results. The sources of error examined include: (1) computational stability in numerical substructure; (2) setup and installation of the physical specimen representing the experimental substructure; and (3) the accuracy of the selected substructuring technique that handles the boundary conditions and continuous exchange of data between the subassemblies. Recommendations are made regarding the effective mitigation of the various sources of errors. It is shown that by controlling errors, hybrid simulation can provide reliable results for collapse simulation by comparison to shake table testing.

Optimization and comparison between two 6-DoF parallel kinematic machines for HIL simulations in wind tunnel

Parallel Robots are for sure the best choice for those applications in which a high accuracy and a high stiffness are required. As a matter of fact the closed-loop kinematic chains that characterize these machines guarantee a very low sensitivity of the end-effector position to the various sources of error. However the working volume of parallel kinematic machines is in general limited with respect to their dimensions. Moreover the reduced mobility range of the passive joints represents a critical aspect that cannot be underestimated. For these reasons PKMs should be optimized for the application they are meant.Given the specifications of the workspace that the machine should be able to cover, it’s necessary to identify an architecture that is suitable for this specific task. This paper describes the optimization process and the comparison between two candidates, the Hexaslide and the Gough-Stewart platform, in order to find out which one is the best choice for a task that requires to reproduce the hydrodynamic effect of sea waves at the bottom of scale models of off-shore wind turbines and boats during HIL simulations in the wind tunnel of the Politecnico di Milano.

Reconstructing land use history from Landsat time-series: Case study of a swidden agriculture system in Brazil

We developed a method to reconstruct land use history from Landsat images time-series. The method uses a breakpoint detection framework derived from the econometrics field and applicable to time-series regression models. The Breaks For Additive Season and Trend (BFAST) framework is used for defining the time-series regression models which may contain trend and phenology, hence appropriately modelling vegetation intra and inter-annual dynamics. All available Landsat data are used for a selected study area, and the time-series are partitioned into segments delimited by breakpoints. Segments can be associated to land use regimes, while the breakpoints then correspond to shifts in land use regimes. In order to further characterize these shifts, we classified the unlabelled breakpoints returned by the algorithm into their corresponding processes. We used a Random Forest classifier, trained from a set of visually interpreted time-series profiles to infer the processes and assign labels to the breakpoints. The whole approach was applied to quantifying the number of cultivation cycles in a swidden agriculture system in Brazil (state of Amazonas). Number and frequency of cultivation cycles is of particular ecological relevance in these systems since they largely affect the capacity of the forest to regenerate after land abandonment. We applied the method to a Landsat time-series of Normalized Difference Moisture Index (NDMI) spanning the 1984–2015 period and derived from it the number of cultivation cycles during that period at the individual field scale level. Agricultural fields boundaries used to apply the method were derived using a multi-temporal segmentation approach. We validated the number of cultivation cycles predicted by the method against in-situ information collected from farmers interviews, resulting in a Normalized Residual Mean Squared Error (NRMSE) of 0.25. Overall the method performed well, producing maps with coherent spatial patterns. We identified various sources of error in the approach, including low data availability in the 90s and sub-object mixture of land uses. We conclude that the method holds great promise for land use history mapping in the tropics and beyond.